A conventional text retrieval method is improved by two additional sources of evidence of relevance: rst, by a passage retrieval method that is based on Hidden Markov Models and second, by a so-called link method which was originally developed for hypertext retrieval. The results show that the two additional sources of evidence improve a conventional vector space retrieval method both in a cons...

In the named entity normalization task, a system identifies a canonical unambiguous referent for names like Bush or Alabama. Resolving synonymy and ambiguity of such names can benefit end-to-end information access tasks. We evaluate two entity normalization methods based on Wikipedia in the context of both passage and document retrieval for question anwering. We find that even a simple normaliz...

Passage retrieval is an essential part of question answering systems. In this paper we use statistical language models to perform this task. Previous work has shown that language modeling techniques provide better results for both, document and passage retrieval. The motivation behind this paper is to define new smoothing methods for passage retrieval in question answering systems. The final ob...

Passage retrieval is an essential part of question answering systems. In this paper we use statistical language models to perform this task. Previous work has shown that language modeling techniques provide better results for both, document and passage retrieval. The motivation behind this paper is to define new smoothing methods for passage retrieval in question answering systems. The long ter...

Passage retrieval consists in identifying short but informative runs of a long text, given a specific user query. We discuss the sources of evidence that help choosing likely high-quality passages, such as relevance to the user query and self-containedness. These measures are different from the traditional information retrieval procedure due to the use of the context of the passage.

In this paper, we present a system for information retrieval of biomedical texts at passage level. Our system used KL-divergence as the underlying retrieval model. We further added query expansion and performed post-processing on the results. We were able to obtain a Document MAP of 0.3563, Passage MAP of 0.0464 and Aspect MAP of 0.2255 on one of the three runs.

Information access in meeting recordings can be assisted by meeting browsers, or can be fully automated following a question-answering (QA) approach. An information access task is defined, aiming at discriminating true vs. false parallel statements about facts in meetings. An automatic QA algorithm is applied to this task, using passage retrieval over a meeting transcript. The algorithm scores ...

In this paper we propose and evaluate a soft computing-based passage retrieval system for Question Answering Systems (QAS). FuzzyPR, our base-line passage retrieval system, employs a similarity measure that attempts to model accurately the question reformulation intuition. The similarity measure includes fuzzy logic-based models that evaluate efficiently the proximity of question terms and dete...

Information retrieval (IR) is finding material (usually documents) of an unstructured nature (usually text) that satisfies an information need from within large collections (usually stored on computers) [1]. The most common and popular information retrieval application is web search engine such as Google[2], Baidu[3], Bing[4] and Sogou[5]. These application will return top-N best retrieval resu...