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2019, The Proceedings of the Annual Convention of the Japanese Psychological Association
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Sem atic Representation on BERT Shin Asakawa and T adahisa Kondo (T okyo wom en's Christian university) Key Words:universal sentence em bedding , sem antic representation, natural lang uag e processing
2014
広島大学比較論理学プロジェクト研究センター研究成果報告書(2013年度)本稿は、2013年9月1日島根県民会館で開催された日本印度学仏教学会第64回学術大会パネル発表A「インド哲学における〈存在〉をめぐる議論の諸相」における発表資料である
IEIC Technical Report …, 2002
Abstract;This paper proposes a method for linguistic steganography in consideration of the meaning of natural language sentences. To describe the meaning of the sentences, this method uses SD-Form, which is a meaning description form consisting of symbols, developed by the ...
Transactions of the Japanese Society for Artificial Intelligence
Though many kinds of multi-agent systems based on argumentation have been proposed where only rule-based knowledge is taken into account, they have been unable to handle the ontological knowledge so far. In our daily life, however, there are a lot of human argumentation where both ontological and rule knowledges are used. For example, in e-commerce, a seller and a buyer usually use ontologies about products along with their respective strategic rules for buying and selling. Recent progress of the Semantic Web technology provides expressive ontology languages. In this paper, we demonstrate integration of the Semantic Web reasoning and argument-based reasoning. We have implemented the integrated system such that Logic of Multiple-valued Argumentation-based agent system (specialized to two values {f, t }) can be accessible to the Semantic Web reasoning established as the description logic reasoning system, given ontologies expressed by OWL DL or its notational variant the DL SHOIN(D). ...
Transactions of the Japanese Society for Artificial Intelligence, 2017
Learning distributed representations for relation instances is a central technique in downstream NLP applications. In particular, semantic modeling of relations and their textual realizations (relational patterns) is important because a relation (e.g., causality) can be mentioned in various expressions (e.g., "X cause Y", "X lead to Y", "Y is associated with X"). Notwithstanding, the previous studies paid little attention to explicitly evaluate semantic modeling of relational patterns. In order to address semantic modeling of relational patterns, this study constructs a new dataset that provides multiple similarity ratings for every pair of relational patterns on the existing dataset [Zeichner 12]. Following the annotation guideline of [Mitchell 10], the new dataset shows a high inter-annotator agreement. We also present Gated Additive Composition (GAC), which is an enhancement of additive composition with the gating mechanism for composing distributed representations of relational patterns. In addition, we conduct a comparative study of different encoders including additive composition, RNN, LSTM, GRU, and GAC on the constructed dataset. Moreover, we adapt distributed representations of relational patterns for relation classification task in order to examine the usefulness of the dataset and distributed representations for a different application. Experiments show that the new dataset does not only enable detailed analyses of the different encoders, but also provides a gauge to predict successes of distributed representations of relational patterns in the relation classification task.
Transactions of The Japanese Society for Artificial Intelligence, 2003
Transactions of The Japanese Society for Artificial Intelligence, 2011
Modeling Reinforcement Learning using an Extended BDI logic TOMATOes
1984, 1948
1984 (en su versión original en inglés: Nineteen Eighty-Four) es una novela política de ficción distópica, escrita por George Orwell entre 1947 y 1948 y publicada el 8 de junio de 1949. La novela popularizó los conceptos del omnipresente y vigilante Gran Hermano o Hermano Mayor, de la notoria habitación 101, de la ubicua policía del Pensamiento y de la neolengua, adaptación del idioma inglés en la que se reduce y se transforma el léxico con fines represivos, basándose en el principio de que lo que no forma parte de la lengua, no puede ser pensado. Muchos analistas detectan paralelismos entre la sociedad actual y el mundo de 1984, sugiriendo que estamos comenzando a vivir en lo que se ha conocido como sociedad orwelliana,1 una sociedad donde se manipula la información y se practica la vigilancia masiva y la represión política y social. Sin embargo, no hay que olvidar que estos elementos ya aparecen en la novela rusa Nosotros (1920) de Zamiatin, en la que se inspiró Orwell, y que se considera la novela fundadora de la novela distópica contemporánea. La novela de 1984 es, sin embargo, mucho más popular y el término «orwelliano» se ha convertido en sinónimo de las sociedades u organizaciones que reproducen actitudes totalitarias y represoras como las representadas en la novela. La novela fue un éxito en términos de ventas y se ha convertido en uno de los más influyentes libros del siglo XX.
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