Document Retrieval assumes that a document is independent of its relevance, and non-relevance. Previous works showed that the same assumption is being considered for passage retrieval in the context of Question Answering. In this paper, we relax this assumption and describe a method for estimating the prior of a passage being relevant, and non-relevant to a question. These prior probabilities a...

This paper describes a new approach to information access that combines techniques from natural language processing and knowledge representation with a new technique for relevance estimation and passage retrieval. Unlike many attempts to combine natural language processing with information retrieval, these results show significant benefit from using linguistic knowledge. Subsumption technology ...

Information Retrieval (IR) and Answer Extraction are often designed as isolated or loosely connected components in Question Answering (QA), with repeated overengineering on IR, and not necessarily performance gain for QA. We propose to tightly integrate them by coupling automatically learned features for answer extraction to a shallow-structured IR model. Our method is very quick to implement, ...

In recent years, dense retrieval has emerged as the primary method for open-domain question-answering (OpenQA). However, previous research often focused on query side, neglecting importance of passage side. We believe that both and sides are equally important should be considered improved OpenQA performance. this paper, we propose a contrastive pseudo-labeled data constructed around passages qu...

The goal of question-oriented text summarization aims at producing the informative short description according to the given queries. This is somewhat similar to the target of question answering which retrieves exact answers from large raw text collections. In this paper, we present a resource, and training data-free summarization model for DUC multi-document summarization task. Similar as last ...

Abstract General concepts are always used to describe query requirement (In the example “What tumor types are associated with Rb1 mutations?”, “Tumor types” is a general concept, and its entity in a relevant documents can be “brain tumor”). To bridge the gaps between concepts in user queries and entities in relevant documents, we proposed a multi-granularity retrieval model in TREC 2007 Genomic...

In this paper, the obtained results on iCLEF-2002 are presented. This is the first time that we try to face up the iCLEF task, and we have used a Passage Retrieval approach, specifically our previously developed system called IR-n. This system previously divides the document in fragments or passages, and after that, the similarity of each passage with the query is measured. Finally, the documen...

Information retrieval (IR) techniques are used in question answering (QA) to retrieve passages from large document collections which are relevant to answering given natural language questions. In this paper we investigate the impact of document segmentation approaches on the retrieval performance of the IR component in our Dutch QA system. In particular we compare segmentations into discourse-b...

We report here on our participation in the 1995 Text Retrieval (TREC 4) conference. This was limited to participation in the interactive searching task due to a re-implementation of our SPIDER retrieval system. We report on two aspects of the SPIDER system that are particularly useful for interactive searching, namely the use of fast query evaluation, and the use of passage highlighting in pres...