Data mining, Information Extraction, Deep Web

DLP is a data security technology that detects and prevents data breach incidents  by monitoring data in-use, in-motion and at-rest.  It has been widely applied for regulatory compliances, data privacy  and intellectual property protection. This talk will introduce basic concepts and security models to describe DLP systems with high level architecture.  DLP is an interesting discipline with content inspection techniques supported by sophisticated algorithms.  Special investigation will be taken for  a few algorithms:  document fingerprinting,  data record fingerprinting, scalable M-pattern string match and etc..

رایانه ها به هنگام ظهور این وعده را دادند که به عنوان یک مخزن دانش و خرد باشند، اما در عوض حجم عظيمی از داده ها را به سوی ما روانه ساختند وب کاوی فرآیند کشف اطلاعات و دانش از داده های وب می باشد. در وب کاوی این داده ها از سمت سرور ، مشتری ، پروکسی سرور یا پایگاه داده سازمان جمع آوری می شود .  روش های وب کاوی  دسته : کاوش محتوای وب ، کاوش ساختار وب و کاوش استفاده از وب تقسيم می شود 3به . زمينه های کاریردی متعددی در وب کاوی وجود دارد از جمله تجارت الکترونيک ، متن کاوی و مدیریت رفتار مشتری .  تحقيقات در زمينه وب کاوی بيشتر بر توسعه تکنيک های  روش اصلی که 3استخراج دانش که برای تحليل داده های وب به کار می روند تمرکز دارد . برای کاوش داده ها در وب به کار می روند شامل: قوانين پيوستگی یا انجمنی ، الگوهای ترتيبی و خوشه بندی می باشند. هدف اصلی کاوش استفاده از وب، جمع آوری اطلاعات راجع به الگوهای پيمایش کاربران می باشد. البته وب کاوی با چالش ها و محدودیت های متنوعی روبه رو است. و در حال حاضر تحقيقات بسياری در زمينه وب کاوی در حال انجام است که هدف آن ها حل این مشکلات می باشد

Deep Web is the data on the internet that is not accessible by popular search engines. It is much greater than the Surface Web we use. Deep Web grants anonymity, and with it, come the horrors of underground misuse. It is a shady (and often very scary) alley of the internet, where criminals run the show. This paper examines how Tor Network, as part of Deep Web, and virtual currency Bitcoin, build an optimal platform for illegal activities online. Moreover, it explores the legal frameworks and gives examples of illegitimate actions that happen just below the surface we browse every day.

Resumen El Presente documento, fue hecho con el propósito de dar a conocer la parte conceptual, qué contiene y cómo se accede a esa parte enorme y oculta bajo la superficie del iceberg llamado " información " que existe en la Red. Se establece la diferencia entre los términos " Deep Web " y " Dark Web " y el propósito por el cual fue creada esta entidad oculta. Se mencionan también algunas composiciones por niveles, y que considero son un mito que viene a completar ese halo de misterio que rodea a la Deep Web. Se da a conocer el tipo de cambio corriente en la Deep Web y su valor real aproximado. Los campos que afecta esta Red Profunda, las herramientas de software de uso común para acceder y se hace hincapié en las precauciones que se deben tener al acceder a la misma.

Özet İnternet şüphesiz insanlık tarihinde devrim niteliğinde bir buluş ve gelişimi de halen devam etmektedir. İnsanların birçoğu iletişim, sosyal medya, alışveriş, siyasi ve sosyal gündem takibi ve daha fazlası için interneti kullanmaktadır. İnternetin devletlerin uluslararası arenada, kamu kuruluşlarında ve insan hayatındaki yeri itibariyle Deep Web ve Dark Web kavramlarının yalnızca bilgisayar, yazılım mühendislerince ele alınmasının eksikliğinden yola çıkarak sosyal bilimler içerisinde incelenmesi büyük önem arz etmektedir. Buradan hareketle çalışma içerisinde Deep Web ve onun karanlık yanı olarak isimlendirilen Dark Web'in ortaya çıkardığı potansiyel tehlikelere değinilmiştir. İki kavramın nasıl ortaya çıktığı ve gelişimi, Deep Web'e erişimin nasıl sağlandığı, iki kavramın birbirinden ince bir çizgiyle ayrıldığı yerler, Dark Web'deki yasadışı faaliyet alanlarının getirmiş olduğu sorunların önemine vurgu yapılmıştır. Akabinde, Dark Web karşısında devletlerin nasıl bir politika izlemesi gerektiğine dair analizler yapılmaya çalışılmıştır. Abstract The Internet is undoubtedly still a revolutionary breakthrough in the history of humanity. Many people use the internet for communication, social media, shopping, political and social agenda, and more. Deep Web and Dark Web concepts not only handled by computer, software engineers but also handled by social siciensists because of the role of internet for the States in international arenas, public institutions and human life. By the moving point that very important

Objective: The paper analyzes money laundering through crypto-assets and offers a legal perspective on how this new technology can be used to commit these felonies. The study intends to shed light on the matter, helping to visualize how future anti-money laundering – AML regulation should focus on tackling crypto criminal activity effectively.

Methodology: The research adopts an inductive approach, bibliographic and documental research technique, with an exploratory and propositional methodological objective.

Results: The paper proposes the following framework of anti-money laundering principles for crypto-focused action: transnational approach for AML action; going beyond basic gatekeeper compliance approach, considering the lack of structural chokepoints in a blockchain protocol; private-sector cooperation and clear AML standards; usage of tracking and reverse-engineering anonymization techniques for the tracing of crypto transaction history; and adoption of a global blacklist for crypto- asset prefixes, preventing money laundering integration.

Contributions: The study addresses a topic that is still unfamiliar in the academic world due to its innovation and complexity, as well as elaborates a set of principles to combat money laundering with crypto-assets that could be of great value to companies and financial institutions.

O presente estudo teve por objetivo propor um processo de mineração de conteúdos em mídias sociais para auxiliar na gestão de destinos turísticos composto por sete fases, elaborado com base nas metodologias propostas por Neves (2013), Hea, Zha e Li (2013), Kalampokis, Tambouris e Tarabanis (2013), Abrahams, Jiao, Fan, Wang e Zhang (2013) e nos modelos de descoberta de conhecimento propostos por Fayyad, Piatetsky-Shapiro e Smyth (1996), Chapman et al. (2000) e Han, Kamber e Pei (2012). Caracteriza-se como pesquisa exploratória e descritiva e como método de investigação foram utilizados métodos mistos. Embora explore o monitoramento nas mídias sociais Facebook, Twitter e YouTube, o processo proposto foi verificado a partir da mineração de conteúdos do Twitter que tivessem os termos da ontologia de aplicação de atrativos e serviços turísticos (hospedagem, alimentação e transportes) das cidades de Curitiba (PR) e Foz do Iguaçu (PR), por opção metodológica e pela dificuldade em obter dados relevantes nas demais mídias sociais investigadas devido a limitações em suas Application Programming Interface (API). O presente processo mostrou-se ser eficaz para coletar conteúdos relevantes e identificar assuntos populares nas mídias sociais, realizar análises quantitativas e qualitativas, bem como auxiliar às Destination Management Organizations – DMO na gestão de destinos turísticos e no processo de tomada de decisões estratégicas e operacionais. Como resultado das análises da utilização das mídias sociais pelas DMO investigadas, constatou-se que o Facebook e o Twitter são mais utilizadas do que o YouTube, que ainda é pouco explorado em relação às demais. Identificou-se ainda que apesar das ações, estratégias e conteúdos publicados serem semelhantes, as abordagens e objetivos variam e os esforços e ações das DMO nas mídias sociais ainda são experimentais. Através das entrevistas semiestruturadas pessoais realizadas com os responsáveis pela gestão e atualização dos perfis em mídias sociais das DMO constatou-se que nenhuma DMO monitora as mídias sociais efetivamente utilizando softwares de monitoramento de mídias sociais ou técnicas de mineração de conteúdos. Entretanto, ainda que superficialmente, as DMO utilizam-se da ferramenta analítica do Facebook para monitorar e analisar o desempenho das ações e publicações. Por fim, foi possível identificar a inexperiência, a falta de conhecimento técnico e de recursos humanos e financeiros como as principais limitações frente a utilização e monitoramento de mídias sociais pelas DMO investigadas. Como sugestão de trabalhos futuros, sugere-se a elaboração do modelo teórico de gestão do conhecimento para que os resultados e conhecimentos obtidos sejam explicitados às instâncias de governança (federal, estadual e municipal), para os demais atores públicos e privados envolvidos na atividade turística, a ampliação das ontologias de aplicação elaboradas e ao monitoramento e mineração de conteúdos em mídias sociais sobre outras organizações turísticas públicas e privadas ou outros eventos como as Olimpíadas no Rio de Janeiro em 2016.


Palavras-chave: turismo; gestão de destinos turísticos; mídias sociais; monitoramento em mídias sociais; mineração de conteúdos em mídias sociais.

The Internet as the whole is a network of multiple computer networks and their massive infrastructure. The web is made up of accessible websites through search engines such as Google, Firefox, etc. and it is known as the Surface Web. The Internet is segmented further in the Deep Web-the content that it is not indexed and cannot access by traditional search engines. Dark Web considers a segment of the Deep Web. It accesses through TOR. Actors within Dark Web websites are anonymous and hidden. Anonymity, privacy and the possibility of non-detection are three factors that are provided by special browser such as TOR and I2P. In this paper, we are going to discuss and provide results about the influence of the Dark Web in different spheres of society. It is given the number of daily anonymous users of the Dark Web (using TOR) in Kosovo as well as in the whole world for a period of time. The influence of hidden services websites is shown and results are gathered from Ahimia and Onion City Dark Web's search engines. The anonymity is not completely verified on the Dark Web. TOR dedicates to it and has intended to provide anonymous activities. Here are given results about reporting the number of users and in which place(s) they are. The calculation is based on IP addresses according to country codes from where comes the access to them and report numbers in aggregate form. In this way, indirect are represented the Dark Web users. The number of users in anonymous networks on the Dark Web is another key element that is resulted. In such networks, users are calculated through the client requests of directories (by TOR metrics) and the relay list is updated. Indirectly, the number of users is calculated for the anonymous networks.

Ogólne zasady poszukiwania informacji w internecie
- Ogólne zasady poszukiwania informacji w internecie
- Sposoby dostępu do zasobów Deep Web
- Zasoby naukowe w Deep Web
- Pozyskiwanie danych, publikacji i treści (w tym naukowych) z Deep Web –  przykłady, studia przypadków

This article tries to explain our rule-based Arabic Named Entity recognition (NER) and classification system. It is based on lists of classified proper names (PN) and particularly on syntactico-semantic
patterns resulting in fine classification of Arabic NE. These patterns use syntactico-semantic combination of morpho-syntactic and syntactic entities. It also uses lexical classification of trigger words and NE
extensions. These linguistic data are essential not only to name entity extraction but also to the taxonomic classification and to determining the NE frontiers. Our method is also based on the contextualisation and
on the notion of NE class attributes and values. Inspired from X-bar theory and immediate constituents, we built a rule-based NER system composed of five levels of syntactico-semantic combination. We also show how the fine NE annotations in our system output (XML database) is exploited in information retrieval and information extraction.

Cyber and its related technologies such as Internet was introduced to the world only in late 1980s, and today it is unimaginable to think of a life without these all pervasive technologies. Despite being ubiquitous around the world, cyber technology is still seen as an enigma by many, mainly due to its rapid development and high level of science involved with it. In addition to the existing complexities of the technology, the level of threat matrix surrounding the cyber domain further lead to various misconceptions and exaggerations apart from elevating the complexity to a few notches above. It is evident that the world in the future is going to be fully dependent on the cyber technology and hence humans are forced to understand this complex domain in order to survive and evolve successfully as 'technological' beings. It is in this context of understanding the enigma around the cyber domain, the book attempts to analyse and disentangle the various issues related to cyber technology. The book also attempts to unravel the various threats that terrorise the cyber world in detail by categorising them according to the perpetrators. The book aims to decrypt the cyber domain and at the same time exhibit the realities in terms of the threat vector, technological sophistication and the rapid development of the domain itself. The book also tries to present the existing reality of cyber environment in India and charts out a few recommendations and suggestions for enhancing the country's cyber security architecture. The eight chapters of the book attempts to decipher the cyber world through detailed analysis of the various issues like hacking, dark web, cyber enabled terrorism, covert cyber capabilities of countries like the US and China apart from studying the cyber environment of India.

When we type the usual www acronym in an electronic device (computer, smartphone, tablet, among others) and then, the address of a webpage, in a matter of seconds we have access to all the information which, without the revolution of technology, would take us days, weeks or months to find. There is no question that Internet has made our life more comfortable and accessible by abruptly changing the way we interact with daily existence but, simultaneously, we have also been exposed to risks which only a few decades ago were fully unimaginable. Again, in the field we are discussing, as we are witnesses and players, reality outdoes fiction.

Software project estimation is important for allocating resources and planning a reasonable work
schedule. Estimation models are typically built using data from completed projects. While organizations
have their historical data repositories, it is difficult to obtain their collaboration due to privacy and
competitive concerns. To overcome the issue of public access to private data repositories this study
proposes an algorithm to extract sufficient data from the GitHub repository for building duration
estimation models. More specifically, this study extracts and analyses historical data on WordPress
projects to estimate OSS project duration using commits as an independent variable as well as an
improved classification of contributors based on the number of active days for each contributor within a
release period. The results indicate that duration estimation models using data from OSS repositories
perform well and partially solves the problem of lack of data encountered in empirical research in software
engineering.

Arguably the biggest challenge in analyzing English tense is to account for the double access interpretation, which arises when a present tensed verb is embedded under a past attitude—e.g. "John said that Mary is pregnant". Present-under-past does not always result in a felicitous utterance, however—cf. "#John believed that Mary is pregnant". While such oddity has been noted, the contrast has never been explained. In fact, English grammars and manuals generally prohibit present-under-past. Work on double access, on the other hand, has either disregarded the oddity (e.g. Abusch 1997: 39) or treated it as a reflex of a particular dialect (e.g. Kratzer 1998: 14). The goal of the paper is to argue—based on a corpus study—that a present-under-past sentence is grammatical, but modulated by two, interacting pragmatic phenomena: cessation and parentheticality.

Coreference resolution plays an important role in Information Extraction.This paper covers the investigation of two strategies based on a mention-pair resolver using Decision Tree classifier on structured and unstructured dataset, targeting coreference resolution in Dari language. Strategies are (1) training separate models which is specialized in particular categories (e.g., lexical, syntactic and semantic) and types of mentions (e.g. pronouns, proper nouns) and (2) using a structured dataset on a machine learning library that is designed to classify numerical values. Moreover, these modifications and comparative models describe a contribution of comprehensive factors involved in the resolution of texts. Specifically, we developed the first Dari corpus ('DariCoref') based on OntoNotes and WikiCoref scheme. Both strategies are produced f-score of state-of-the-art.

In this paper, we outline our work on developing a disk-based infrastructure for efficient visualization and graph exploration operations over very large graphs. The proposed platform, called graphVizdb, is based on a novel technique for indexing and storing the graph. Particularly, the graph layout is indexed with a spatial data structure, i.e., an R-tree, and stored in a database. In runtime, user operations are translated into efficient spatial operations (i.e., window queries) in the backend.

ABSTRCT Market Situation is something that will provide valuable benefits to increase the productivity of selling a product both conventionally and online, Indonesian e-commerce map data in the second quarter shows that the increase in sales of goods and services online is increasing, it was seen from 3 (three) major e-marketplaces namely Tokopedia, Shopee, and Bukalapak, then e-commerce activities in Indonesia in January 2019 for purchasing products or service online by 86%, it means that 86% of activities will buy products and services which located in Indonesian e-commerce. This situation creates fierce competition for sellers or business people or entrepreneurs who are just starting their business. One way for sellers to get a primacy in this competition is to apply segmentation to the products that they will sell in the online shop, but the data from a study by the association revealed that if a product stays online for a long time (more than 550 days) then 78% is very likely not to be purchased, the product placement activity in the online shop must be segmented appropriately, this research provided an effort to apply data extraction technology with web crawlers to present the segmentation, and the results of prototype testing to 9 entrepreneurs, 210 students who will start an online business, and 19 private employees which produce web crawler technology testing to help product segmentation with the result of successful was 79% with the Good category in laying online product was segmented. ABSTRAK Keadaan Pasar adalah suatu hal yang akan memberikan manfaat yang berharga untuk meningkatkan produktivitas penjualan suatu produk baik secara konvensional maupun secara online, data peta e-commerce indonesia pada kuartal ke 2 (dua) meperlihatkan bahwa peningkatan penjualan barang dan jasa secara online meningkat, dilihat dari 3 (tiga) besar e-marketplace yaitu tokopedia, shopee dan bukalapak, kemudian di sertai aktivitas e-commerce di indonesia pada januari 2019 untuk pembelian produk atau jasa online sebesar 86 %, artinya aktivitas sebesar 86% akan membeli produk dan jasa yang berada di e-commerce indonesia. Keadaan ini menimbulkan persaingan ketat untuk para penjual atau pebisnis maupun penggiat wirausaha yang baru memulai usahanya, salah satu cara agar penjual mendapatkan keunggulan dalam bersaing ini adalah dengan menerapkan segmentasi pada produk yang akan mereka jual di online shop, akan tetapi data dari sebuah penelitian oleh asosiasi yang mengungkapkan bahwa jika sebuah produk tetap online untuk waktu lama (lebih dari 550 hari) maka 78 % sangat mungkin tidak akan dibeli, seharusnya aktivitas peletakan produk di online shop harus tersegmentasi secara tepat, peneliti ini memberikan upaya penerapan teknologi ekstraksi data dengan web crawler untuk menyajikan segmentasi tersebut, dan hasil pengujian prototipe kepada 9 wirausaha , 210 mahasiswa yang akan memulai usaha online, dan 19 pegawai swasta menghasilkan pengujian teknologi web crawler untuk membantu segmentasi produk dengan hasil kesuksesan informasi segmentasi sebesar 79 % dengan kategori Baik untuk digunakan dalam peletakan produk online yang tersegmentasi.

Semantically, objects in unstructured document are related each other to perform a certain entity relation. This certain entity relation such: drug-drug interaction through their compounds, buyer-seller relationship through the goods or services, etc. Motivated by that kind of interaction, this study proposes a method to extract those objects and their interactions. It is presented a general framework of object-interaction mining of large corpora. The framework is started with the initial step in extracting a single object in the unstructured document. In this study, the initial step is a pattern learning method that is applied to drug-label documents to extract drug-names. We utilize an existing external knowledge to identify a certain regular expressions surrounding the targeted object and the probabilities of that regular expression, to perform the pattern learning process. The performance of this pattern learning approach is promising to apply in this relation extraction area. As presented in the results of this study, the best f-score performance of this method is 0.78 f-score. With adjusting of some parameters and or improving the method, the performance can be potentially improved

With the rapid growth of users in social networking services, data is generated in thousands of terabytes every day. Practical frameworks for data extraction from social networking sites have not been well investigated yet. In this paper, a methodology for data extraction with respect to Sina Weibo is discussed. In order to design a proper method for data extraction, the properties of complex networks and the challenges when extracting data from complex networks are discussed first. Then, the reason for choosing Sina Weibo as the data source is given. After that, the methods for data gathering are introduced and the techniques for data sampling and data clean-up are discussed. Over 1 million users and hundreds of millions of social relations between them were extracted from Sina Weibo using the methods proposed in this paper.

ABSTRAK Berdasarkan situs wearesocial.com menunjukan data perkembangan pengguna internet sebesar 4.437 miliar yang disertai 75 % pembelian produk online, 82 % pencarian produk dan kunjungan on-line retail 92% yang kemudian memicu sebuah penelitian oleh asosiasi yang mengungkapkan bahwa jika sebuah produk tetap online untuk waktu lama (lebih dari 550 hari) maka 78 % sangat mungkin tidak akan dibeli, seharusnya aktivitas peletakan produk di online shop harus tersegmentasi secara tepat, karena segmentasi produk yang baik akan meningkatkan potensi e-commerce atau e-marketplace pada tingkat negara seperti meningkatkan efisiensi pasar, efesiensi operational, memperluas akses terhadap pasar, dan adanya keterkaitan, selanjutnya dari tren tersebut maka peneliti membuat suatu teknologi script otomatis atau program untuk menulusuri situs-situs e-marketplace indonesia, teknologi ini dikenal dengan nama web crawler atau web spider, dan peneliti mengimplementasikan sebuah prototipe teknologi yang dapat menganalisis teks-teks dari produk yang diletakan di e-marketplace Indonesia, dan menghasilkan clustering segmentasi pasar sebagai solusi yang efektif untuk pelaku bisnis yang akan meletakan produknya di e-commerce maupun di e-marketplace, sehingga akan mendapatkan keunggulan bersaing guna mencapai Store Image yang baik bagi pelaku bisnis di indonesia. ABSTRACT Based on the site wearesocial.com shows data on the development of internet users amounting to 4,437 billion accompanied by 75% of purchases of online products, 82% of product searches and 92% on-line retail visits which then triggered a study by an association that revealed that a product remained online for time long time (more than 550 days), 78% is very unlikely to be purchased, the product laying activity in the online shop should be segmented appropriately, because good product segmentation will increase the potential of e-commerce or e-marketplace at the country level such as increasing market efficiency , operational efficiency, expanding access to the market, and linkages, then from that trend, the researcher makes an automated script technology or program to track Indonesian e-marketplace sites, this technology is known as web crawlers or web spiders, and researchers implement a technology prototype that can analysis of texts from products placed in Indonesian e-marketplace, and produce clustering market segmentation as an effective solution for business people who will put their products in e-commerce and in e-marketplace, so that they will gain competitive advantages to reach the Store Image good for business people in Indonesia.

The Islamic State of Iraq and Syria (ISIS) has made great use of the Internet and online social media sites to spread its message and encourage others, particularly young people, to support the organization; to travel to the Middle East to engage in combat, fighting side-by-side with other jihadists; or to join the group by playing a supporting role, which is often the role carved out for young women who are persuaded to join ISIS. Today, in the field of fighting the ideology of extremism and terrorism, the main concern is that of the vast spreading of propaganda of the "Islamic State" primarily through the Internet. ISIS propaganda is now more frequently aimed at Westerners and more specifically at the “Millennial generation”, spreading i.e. the idea of what the real Salafi Islam is and how to fight and destroy the "unconventional Islam” which takes on board western principles. Clearly, social media has proven to be an extremely valuable tool for the terrorist organization and is perfectly suited for the very audience it intends to target. Increasingly, ISIS’ posts on websites include sophisticated, production-quality videos and images which incorporate visual effects.
Which messages from jihadists induce young Westerners to become involved with the terrorist group? What convinces young people from Europe, Australia, Canada, and the United States, many of whom run away from home still in their teens, to leave their homelands to join ISIS on the battlefield? Which risks does a home country face when its nationals communicate and establish relationships with members of ISIS? Could the jihadist social network propaganda machine be shut down? Weighing all factors, is stopping ISIS rhetoric on the Internet the best course of action? To understand the project, several propaganda documents coming from sources inside the Daesh were analysed to identify the online grooming to recruit Jihadists and the instructions to follow to win respect in the Arabian world.

Due to the enormous amount of data stored in databases and within other several information resources warehouses, there're increased needs to new technology to extract the hidden valuable knowledge from this data. This knowledge became too hard to extract by traditional techniques and so there're big problem in managing this useful information. Data mining techniques are an effective solution to such a problem. This paper will investigate in the possible Internet fields and applications that can use data mining to enhance the efficiency of its works and to increase its performance.

In Natural Language Processing, Parts-of-Speech tagging plays a vital role in text processing for any sort of language processing and understanding by machine. In each of the quarter of machine translation, information retrieval or speech processing, it becomes obligatory for the analysis thereafter. This paper proposes a rule based Parts-of-Speech tagger for Bangla with different stages of tagging. The paper also suggests one level higher tagging after identifying the parts of speech. We call this level as emotion tagging. The following diagram represents the proposed labeling of POS tagging in this paper.

Aquilo que muitos conhecem popularmente como Internet, caracteriza-se, socioculturalmente como ciberespaço e possui territorialidade própria, bem como suas próprias práticas culturais, identificadas como cibercultura. Tendo em vista que, para trazer à luz percepções fundamentais acerca de determinados territórios faz-se necessário analisá-los sob diferentes óticas, contemplando dimensões tais como a política, a econômica, a social e a cultural, este artigo tem como objetivo a realização de um estudo exploratório sobre a territorialidade digital do ciberespaço, por meio de pesquisa bibliográfica e análise de conteúdo, de modo a examinar e destacar aspectos socioculturais a partir das alterações promovidas pela Web 2.0 e percepções sobre as frações do ciberespaço designadas genericamente de Deep Webe Dark Web.

Natural Language Processing is a programmed approach to analyze text that is based on both a set of theories and a set of technologies. This forum aims to bring together researchers who have designed and build software that will analyze, understand, and generate languages that humans use naturally to address computers.

El artículo aborda la pendulación entre libre circulación de la información y la privacidad vs. la seguridad y el control, que se produce por los fuertes intereses que intervienen en ambos polos. Frente al caso de la Deep Web, por su ambigüedad intrínseca, la posición de la sociedad civil que es ajena a ella levanta las banderas de uno y otro lado. Relacionar esta pendulación con la Deep Web y los espacios de internet permite que los Estados nacionales y su legislación actualicen su rol de soberanos sobre las sociedades que representan. Las posiciones más duras de este conflicto, en orden de jerarquía, están encarnadas en las potencias mundiales y los motores de búsquedas y navegadores más populares. A nivel de la sociedad civil, además de los que navegan por la superficie, encontramos los que utilizan la Deep Web como herramienta de información y comunicación segura y los que la utilizan para delinquir.

Web is a wide, various and dynamic environment in which different users publish their documents. Web-mining is one of data mining applications in which web patterns are explored. Studies on web mining can be categorized into three classes: application mining, content mining and structure mining. Today, internet has found an increasing significance. Search engines are considered as an important tool to respond users' interactions. Among algorithms which is used to find pages desired by users is page rank algorithm which ranks pages based on users' interests. However, as being the most widely used algorithm by search engines including Google, this algorithm has proved its eligibility compared to similar algorithm, but considering growth speed of Internet and increase in using this technology, improving performance of this algorithm is considered as one of the web mining necessities. Current study emphasizes on Ant Colony algorithm and marks most visited links based on higher amount of pheromone. Results of the proposed algorithm indicate high accuracy of this method compared to previous methods. Ant Colony Algorithm as one of the swarm intelligence algorithms inspired by social behavior of ants can be effective in modeling social behavior of web users. In addition, application mining and structure mining techniques can be used simultaneously to improve page ranking performance.

The Internet may be free, but service provider’s indispensable to access services are not, to the extent that while the complexity and burden of the sites increases, it is becoming more and more expensive to surf the net. Blocking access under the guise of protecting us from offensive or sexually explicit content, to pages, chat rooms, newsgroups and other Web options is not anymore an excuse, but a lie. Government surveillance in the Internet, uncontrolled practices of data harvesting and restriction of free speech, open discussion of issues and even political activism has spread in the last 20 years to include countries that are considered democracies such as the U.S. Internet has become a battleground of power and therefore become increasingly militarized.

In this paper, we present a system for personality recognition that exploits linguistic cues and does not require supervision for evaluation. We run the system on a dataset sampled from a popular Social Network: FriendFeed. We adopted the five classes from the standard model known in psychology as the "Big Five": extraversion, emotional stability, agreeableness, conscientiousness and openness to experience. Making use of the linguistic features associated with those classes the system generates one personality model for each user. The system then evaluates the models by comparing all the posts of one single user (users that have only one post are discarded). As evaluation measures the system provides accuracy (measure of the reliability of the personality model) and validity (measure of the variability of writing style of a user). The analysis of a sample of 748 Italian users of FriendFeed showed that that the most frequent personality type is represented by the model of an extravert, insecure, agreeable, organized and unimaginative person.

The gigantic growth of information on the Internet makes discovery information challenging and time consuming. We are encircled by a plethora of data in the form of blogs, papers, reviews, and comments on different websites. Recommender systems endow a solution to this situation by automatically capturing user interests and recommending respective information the user may also find relevant. The purpose of developing recommender systems is to detract information overload by retrieving the most pertinent knowledge and services from an enormous amount of data, thereby providing personalized services. The most vital feature of a recommender system is its proficiency to "supposition" a user's preferences and interests by examining the behavior of this user and/or the behavior of other users to originate personalized recommendations. So several research works have been done in this area, but nothing consolidated has been appraised. In this paper, we are going to discuss a brief summary of imperfection in the available recommender system. We are also trying to figure out these shortcomings of the available recommender system to generate a new method that improves these shortcomings.

Attended Software Freedom Kosova 2016 conference. Held in Pristina, Kosovo (October 2016). Received a full speaker grant from the conference organizers and presented a lecture titled “Using public library computers anonymously in order to access digital libraries in the deep web” For more info please visit http://sfk.flossk.org/sfk16/speaker-detail.php?speakerId=33

The World Wide Web organizes information in semi-structured HTML documents. For a template-based web page that contains a list of items, information schema can be implied and structured data can be extracted with a query, i.e. a (web) wrapper. When a user interface gets updated, the document structure changes, and the wrapper has a tendency to break.

Extracting structured data from multiple data records in a robust way from a single web page is the subject of this project. Current state-of-the-art methods allow to detect template-based data regions on a page, to extract data from a single data record in a robust way, and repeatedly extract data from multiple records.

In this thesis, we have combined the three ideas into a new method, which deals with building a robust record-level wrapper from a single user-annotated web page. We have designed, implemented, and tested the algorithm. Experimental results using a large number of web pages from multiple domains show, that the proposed approach works with high precision and within reasonable execution time on commodity hardware.

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure, called the text chart. We describe details of the integration methods, and show how information extraction and language checking applications for realworld German text benefit from a deep grammatical analysis.

ste artigo apresenta uma análise dos dados coletados na Deep Web, discutindo  suas  expressões  a  partir  dos  conceitos  de  Disciplina (FOUCAULT,    2010)    e    Dialética    do    Esclarecimento    (ADORNO; HORKHEIMER,  1985).  Este  espaço  virtual  é  caracterizado  por  ser amplamente  protegido  de  identificações  por  parte  das  autoridades, permitindo a utilização dos seus internautas sem consequências legais e sociais o que potencializa expressões e ideias que seriam reprimidas em um ambiente no qual a verificação do autor fosse percebida. Assim sendo,  por  meio  de  uma  pesquisa  exploratória,  navegou-se  pelo ambiente observando os principais sítios virtuais e, por meio da análise destes,  considerou-se  que  os  reiterados  espaços  de  manifestação apontam  para  a  compreensão  de  que  nosso  atual  avanço  tecnológico ainda contrasta com a barbárie que, reprimida socialmente, expressa-se no submundo da internet.

There are several methods and available tools for terminology extraction, but the quality of the extracted terms is not always high. Hence, an important consideration in terminology extraction is to assess the quality of the extracted terms. In this paper, we propose and make available a tool for annotating the correctness of terms extracted by three term-extraction tools. This tool facilitates term annotation by using a domain-specific dictionary, a set of filters, and an annotation memory, and allows for post-hoc evaluation. We present a study in which two human judges used the developed tool for term annotation. Their annotations were then analyzed to determine the efficiency of term extraction tools by measures of precision, recall, and F-score, and to calculate the inter-annotator agreement rate.

Popular Personalities have multiple name aliases addressed in different documents of the web. An exact textual web identification of a person is useful in information retrieval, sentiment analysis, relation extraction and name disambiguation. Accurate alias extraction of a person would never be completed unless there must be a formal mechanism to collect various alias names dispersed over the entire web spider. This is a difficult task since web is an unstructured electronic medium, and also web content writers have the freedom to write names with different spell characters but with the same pronunciation. Hence this task is possible only by a focused crawler spanning the web corpora for a large amount of time. Proposed algorithm eliminates noisy aliases to a greater extent. In this paper, proposed approach has shown significant improvement in F-Score compared to existing alias extraction method.