Passage retrieval is usually defined as the task of searching for passages which may contain the answer for a given query. While these approaches are very e cient when dealing with texts, applied to log files (i.e. semi-structured data containing both numerical and symbolic information) they usually provide irrelevant or useless results. Nevertheless one appealing way for improving the results ...

This report describes a new open-domain answer retrieval system developed at the University of Edinburgh and gives results for the TREC-12 question answering track. Phrasal answers are identified by increasingly narrowing down the search space from a large text collection to a single phrase. The system uses document retrieval, query-based passage segmentation and ranking, semantic analysis from...

This report presents the work carried out at NLE Lab for the CLEF-IP 2009 competition. We adapted the JIRS passage retrieval system for this task, with the objective to exploit the stylistic characteristics of the patents. Since JIRS was developed for the Question Answering task and this is the first time its model was used to compare entire documents, we had to carry out some transformations o...

We describe the process that led to the our participation in the INEX 2011 Prove It task. We submitted the results of six book page retrieval systems over a collection of 50,000 books. Two of our runs use the sequential dependency model (a model that uses both unigrams and bigrams from a query) and the other four interpolate between language model scores at the passage level and sequential depe...

Open-Domain Question Answering systems (QA) performs the task of detecting text fragments in a collection of documents that contain the response to user’s queries. These systems use high complexity tools that reduce its applicability to the treatment of small amounts of text. Consequently, when working on large document collections, QA systems apply Information Retrieval (IR) techniques to redu...

While developing an approach towhy-QA, we extended a passage retrieval system that uses offthe-shelf retrieval technology with a re-ranking step incorporating structural information. We get significantly higher scores in terms of MRR@150 (from 0.25 to 0.34) and success@10. The 23% improvement that we reach in terms of MRR is comparable to the improvement reached on different QA tasks by other r...

I describe my participation on the 2015 edition of the BioASQ challenge in which I submitted results for the concept matching, document retrieval, passage retrieval, exact answer and ideal answer subtasks. My approach relies on a in-memory based database (IMDB) and its built-in text analysis features, as well as on PubMed for retrieving relevant citations, and on predefined ontologies and termi...

Long gram-based indices are experimented at NTCIR-4 patent task. No morphological analyses are required to make gram-based indices. The ABJ and DEJ tag fields are extracted and indexed from NTCIR-4 patent corpus. Passages are extracted and indexed also. The total index size is 240Gbyte and time to make indices is about 86 hours. By merging the result of passage retrieval with the result of docu...

The present study was designed to determine whether the increased recall of pictures across repeated tests (hypermnesia) is due to increasing strength of imaginal traces during the retention interval or to increased retrieval practice from prior tests. Subjects studied 60 pictures and then recalled them after various delays that were filled with instructions and, in two cases, reading a passage...

The HARD track of TREC 2004 aims to improve the accuracy of information retrieval through the use of three techniques: (1) query metadata that better describes the information need, (2) focused and time-limited interaction with the searcher through “clarification forms”, and (3) incorporation of passage-level relevance judgments and retrieval. Participation in all three aspects of the track was...