A speech-based just-in-time retrieval system using semantic search
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: Systems Demonstrations
Using a Wikipedia-based semantic relatedness measure for document clustering
TextGraphs-6 Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing
A just-in-time document retrieval system for dialogues or monologues
SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
Harnessing different knowledge sources to measure semantic relatedness under a uniform model
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Computing text semantic relatedness using the contents and links of a hypertext encyclopedia
Artificial Intelligence
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
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A network of concepts is built from Wikipedia documents using a random walk approach to compute distances between documents. Three algorithms for distance computation are considered: hitting/commute time, personalized page rank, and truncated visiting probability. In parallel, four types of weighted links in the document network are considered: actual hyperlinks, lexical similarity, common category membership, and common template use. The resulting network is used to solve three benchmark semantic tasks – word similarity, paraphrase detection between sentences, and document similarity – by mapping pairs of data to the network, and then computing a distance between these representations. The model reaches state-of-the-art performance on each task, showing that the constructed network is a general, valuable resource for semantic similarity judgments.