This paper presents a transductive approach to learn ranking functions for extractive multi-document summarization. At the first stage, the proposed approach identifies topic th...
Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dim...
We investigate using topic prediction data, as a summary of document content, to compute measures of search result quality. Unlike existing quality measures such as query clarity t...
Background: We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document ...
Episodic knowledge is often stored in the form of textual narratives written in natural language. However, a large repository of such narratives will contain both repetitive and n...