This paper presents most used user models and inductive methods based on probability. It describe... more This paper presents most used user models and inductive methods based on probability. It describes a typical usage of user modelling in a complex recommender system and propose a new contribution to probabilistic user modelling. Some initial experiments are also presented.
... Basic idea of the Fagin, Lotem, Naor model is preserved, we assume that objects are repeatedl... more ... Basic idea of the Fagin, Lotem, Naor model is preserved, we assume that objects are repeatedly appearing in different repositories and can be accessed in a mono ... 6: [o, oai] = Serveri. sequentialAccess(fs[i], depth); 7: tai = oai; {Update threshold} 8: for all j = 0...m, j = i do {Get all ...
In this paper, we describe area of recommender systems, with focus on user preference learning pr... more In this paper, we describe area of recommender systems, with focus on user preference learning problem. We describe such system and identify some interesting problems. We will compare how well different approaches cope with some of the problems. This paper may serve as an introduction to the area of user preference learning with a hint on some interesting problems that have not been solved yet.
PrefWork is a framework for testing of methods of induction of user preferences. PrefWork is thor... more PrefWork is a framework for testing of methods of induction of user preferences. PrefWork is thoroughly described in this paper. A reader willing to use Pref-Work finds here all necessary information -sample code, configuration files and results of the testing are presented in the paper. Related approaches for data mining testing are compared to our approach. There is no software available specially for testing of methods for preference learning to our best knowledge.
We describe two approaches for the visualisation of provenance -one using natural language genera... more We describe two approaches for the visualisation of provenance -one using natural language generation to produce texts, the other using a graphical approach. Our main contribution is a mechanism using a combination of these modalities.
Web Semantics: Science, Services and Agents on the World Wide Web, 2014
The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a pla... more The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to authoring and accessing metadata within the VRE. Using evidence gathered from data provided by the users of the system we discuss the lessons learnt from deployment with three case study groups.
ABSTRACT In this demo we present ourSpaces, a Virtual Research Environment designed to support in... more ABSTRACT In this demo we present ourSpaces, a Virtual Research Environment designed to support inter-disciplinary research teams. This system has been developed to facilitate collaboration and interaction between researchers by enabling users to create, visualise and manage the provenance of research artefacts and processes.
18th International Conference on Database and Expert Systems Applications (DEXA 2007), 2007
Page 1. Fusing Data and Optimizing Queries for Intelligent Search Václav Snáel , Pavel Krömer FE... more Page 1. Fusing Data and Optimizing Queries for Intelligent Search Václav Snáel , Pavel Krömer FEECS, Dept. of Computer Science VB Technical University of Ostrava 17. listopadu 15,CZ 708 33 OstravaPoruba, Czech Republic {pavel.kromer.fei, vaclav.snasel}@vsb.cz ...
In this paper, we describe area of recommender systems, with focus on user preference learning pr... more In this paper, we describe area of recommender systems, with focus on user preference learning problem. We describe such system and identify some interesting problems. We will compare how well different approaches cope with some of the problems. This paper may serve as an introduction to the area of user preference learning with a hint on some interesting problems that have not been solved yet.
The task of similarity search is widely used in various areas of computing, including multimedia ... more The task of similarity search is widely used in various areas of computing, including multimedia databases, data mining, bioinformatics, social networks, etc. For a long time, the database-oriented applications of similarity search employed the definition of similarity restricted to metric distances. Due to the metric postulates (reflexivity, non-negativity, symmetry and triangle inequality), a metric similarity allows to build a metric index above the database which can be subsequently used for efficient (fast) similarity search. On the other hand, the metric postulates limit the domain experts (providers of the similarity measure) in similarity modeling. In this paper we propose an alternative non-metric method of indexing for efficient similarity search. The requirement on metric is replaced by the requirement on fuzzy similarity satisfying the transitivity property with a tuneable fuzzy conjunctor. We also show a duality between the fuzzy approach and the metric one.
The main topic of this paper is description of a proposal of a web shop with user preference sear... more The main topic of this paper is description of a proposal of a web shop with user preference searching - PrefShop. A typical web shop was implemented, but new capabilities were added to help the user with finding desired object. Besides preference search, visual hints that clarify the object relevance or the lack of relevance are proposed.
Web search heuristics based on Fagin 's threshold algorithm assume we have the user profile in th... more Web search heuristics based on Fagin 's threshold algorithm assume we have the user profile in the form of particular attribute ordering and a fuzzy aggregation function representing the user combining function. Having these, there are sufficient algorithms for searching top-k answers. Finding particular attribute ordering and aggregation for a user still remains a problem. In this short paper our main contribution is a proof of concept of a new iterative process of acquisition of user preferences and attribute ordering.
This paper presents most used user models and inductive methods based on probability. It describe... more This paper presents most used user models and inductive methods based on probability. It describes a typical usage of user modelling in a complex recommender system and propose a new contribution to probabilistic user modelling. Some initial experiments are also presented.
... Basic idea of the Fagin, Lotem, Naor model is preserved, we assume that objects are repeatedl... more ... Basic idea of the Fagin, Lotem, Naor model is preserved, we assume that objects are repeatedly appearing in different repositories and can be accessed in a mono ... 6: [o, oai] = Serveri. sequentialAccess(fs[i], depth); 7: tai = oai; {Update threshold} 8: for all j = 0...m, j = i do {Get all ...
In this paper, we describe area of recommender systems, with focus on user preference learning pr... more In this paper, we describe area of recommender systems, with focus on user preference learning problem. We describe such system and identify some interesting problems. We will compare how well different approaches cope with some of the problems. This paper may serve as an introduction to the area of user preference learning with a hint on some interesting problems that have not been solved yet.
PrefWork is a framework for testing of methods of induction of user preferences. PrefWork is thor... more PrefWork is a framework for testing of methods of induction of user preferences. PrefWork is thoroughly described in this paper. A reader willing to use Pref-Work finds here all necessary information -sample code, configuration files and results of the testing are presented in the paper. Related approaches for data mining testing are compared to our approach. There is no software available specially for testing of methods for preference learning to our best knowledge.
We describe two approaches for the visualisation of provenance -one using natural language genera... more We describe two approaches for the visualisation of provenance -one using natural language generation to produce texts, the other using a graphical approach. Our main contribution is a mechanism using a combination of these modalities.
Web Semantics: Science, Services and Agents on the World Wide Web, 2014
The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a pla... more The ourSpaces Virtual Research Environment makes use of Semantic Web technologies to create a platform to support multi-disciplinary research groups. This paper introduces the main semantic components of the system: a framework to capture the provenance of the research process, a collection of services to create and visualise metadata and a policy reasoning service. We also describe different approaches to authoring and accessing metadata within the VRE. Using evidence gathered from data provided by the users of the system we discuss the lessons learnt from deployment with three case study groups.
ABSTRACT In this demo we present ourSpaces, a Virtual Research Environment designed to support in... more ABSTRACT In this demo we present ourSpaces, a Virtual Research Environment designed to support inter-disciplinary research teams. This system has been developed to facilitate collaboration and interaction between researchers by enabling users to create, visualise and manage the provenance of research artefacts and processes.
18th International Conference on Database and Expert Systems Applications (DEXA 2007), 2007
Page 1. Fusing Data and Optimizing Queries for Intelligent Search Václav Snáel , Pavel Krömer FE... more Page 1. Fusing Data and Optimizing Queries for Intelligent Search Václav Snáel , Pavel Krömer FEECS, Dept. of Computer Science VB Technical University of Ostrava 17. listopadu 15,CZ 708 33 OstravaPoruba, Czech Republic {pavel.kromer.fei, vaclav.snasel}@vsb.cz ...
In this paper, we describe area of recommender systems, with focus on user preference learning pr... more In this paper, we describe area of recommender systems, with focus on user preference learning problem. We describe such system and identify some interesting problems. We will compare how well different approaches cope with some of the problems. This paper may serve as an introduction to the area of user preference learning with a hint on some interesting problems that have not been solved yet.
The task of similarity search is widely used in various areas of computing, including multimedia ... more The task of similarity search is widely used in various areas of computing, including multimedia databases, data mining, bioinformatics, social networks, etc. For a long time, the database-oriented applications of similarity search employed the definition of similarity restricted to metric distances. Due to the metric postulates (reflexivity, non-negativity, symmetry and triangle inequality), a metric similarity allows to build a metric index above the database which can be subsequently used for efficient (fast) similarity search. On the other hand, the metric postulates limit the domain experts (providers of the similarity measure) in similarity modeling. In this paper we propose an alternative non-metric method of indexing for efficient similarity search. The requirement on metric is replaced by the requirement on fuzzy similarity satisfying the transitivity property with a tuneable fuzzy conjunctor. We also show a duality between the fuzzy approach and the metric one.
The main topic of this paper is description of a proposal of a web shop with user preference sear... more The main topic of this paper is description of a proposal of a web shop with user preference searching - PrefShop. A typical web shop was implemented, but new capabilities were added to help the user with finding desired object. Besides preference search, visual hints that clarify the object relevance or the lack of relevance are proposed.
Web search heuristics based on Fagin 's threshold algorithm assume we have the user profile in th... more Web search heuristics based on Fagin 's threshold algorithm assume we have the user profile in the form of particular attribute ordering and a fuzzy aggregation function representing the user combining function. Having these, there are sufficient algorithms for searching top-k answers. Finding particular attribute ordering and aggregation for a user still remains a problem. In this short paper our main contribution is a proof of concept of a new iterative process of acquisition of user preferences and attribute ordering.
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Papers by Alan Eckhardt