Relational clustering has received much attention from researchers in the last decade. In this paper we present a parametric method that employs a combination of both hard and soft clustering. based on the correspondi...
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WordNet, a widely used sense inventory for Word Sense Disambiguation(WSD), is often too fine-grained for many naturallanguage applications because of its narrow sense distinctions. We present a semi-supervised approa...
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Word Sense Disambiguation (WSD) is a well-known problem in the naturallanguageprocessing. In recent years, there has been increasing interest in applying neural networks and machine learning techniques to solve WSD ...
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Despite the clear inter-dependency between analyzing the interactions in social networks, and analyzing the naturallanguage content of these interactions, these aspects are typically studied independently. In this pa...
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After recasting the computation of a distributional thesaurus in a graph-based framework for term similarity, we introduce a new contextualization method that generates, for each term occurrence in a text, a ranked li...
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We propose a simple graph-based method for word sense disambiguation (WSD) where sense and context embeddings are constructed by applying the Skip-gram method to random walks over the sense graph. We used this method ...
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Many organizations possess large collections of textual reports that document how a problem is solved or analysed, e.g. medical patient records, industrial accident reports, lawsuit records and investigation reports. ...
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We discuss several feature sets for novelty detection at the sentence level, using the data and procedure established in task 2 of the TREC 2004 novelty track. In particular, we investigate feature sets derived from g...
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This paper describes the system designed by the Baidu PGL Team which achieved the first place in the Textgraphs 2020 Shared Task. The task focuses on generating explanations for elementary science questions. Given a q...
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Generating domain-specific content such as legal clauses based on minimal user-provided information can be of significant benefit in automating legal contract generation. In this paper, we propose a controllable graph...
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