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Using Wikipedia at the TREC QA Track

David Ahn, Valentin Jijkoun, Gilad Mishne, Karin Müller, Maarten de Rijke, Stefan Schlobach
2004 Text Retrieval Conference  
We describe our participation in the TREC 2004 Question Answering track.  ...  This year we made essential use of Wikipedia, the free online encyclopedia, both as a source of answers to factoid questions and as an importance model to help us identify material to be returned in response  ...  Acknowledgments This research was supported by the Netherlands Organization for Scientific Research (NWO) under project numbers 017.001.190, 220-80-001, 264-70-050, 612-13-001, 612.000.106, 612.000.207  ... 
dblp:conf/trec/AhnJMMRS04 fatcat:w6xpz35pk5bghblw4kwfmbtr7y

Tianwang at TREC 2006 QA Track

Jing He, Yuan Liu
2006 Text Retrieval Conference  
This paper describes the architecture and implementation of Tianwang QA system2006, which works for the TREC QA Main task this year.  ...  And such query generation algorithm can be benefit from both Frequent Asked Questions on Web and past TREC QA data.  ...  The reason for this is two-folded: first of all, the knowledge base of Wikipedia contains large quantity of pages, most of which are not useful in this Figure1: Tianwang QA System 2006 infrastructure TREC  ... 
dblp:conf/trec/HeL06 fatcat:itzuonrxfnb2zdh23qa7y472uy

Ask the Crowd to Find out What's Important

Sisay Fissaha Adafre, Maarten de Rijke
2007 Seventh IEEE International Conference on Data Mining Workshops (ICDMW 2007)  
Second, we provide multiple types of empirical evidence for the usefulness of this notion of typical-information-for-acategory for estimating the importance of sentences.  ...  First, we introduce the idea of using the increasing amount of manually labeled category information (that is becoming available through collaborative knowledge creation efforts) to identify "typical information  ...  We took 29 topics from TREC 2005 QA track that have corresponding Wikipedia articles.  ... 
doi:10.1109/icdmw.2007.99 dblp:conf/icdm/AdafreR07 fatcat:fxm7abf5erfengio5gqqkqqk2m

Towards a Multi-Stream Question Answering-As-XML-Retrieval Strategy

David Ahn, Sisay Fissaha Adafre, Valentin Jijkoun, Karin Müller, Maarten de Rijke, Erik F. Tjong Kim Sang
2005 Text Retrieval Conference  
We describe our participation in the TREC 2005 Question Answering track; our main focus this year was on improving our multi-stream approach to question answering and on making a first step towards a question  ...  We provide a detailed account of the ideas underlying our approaches to the QA task, report on our results, and give a summary of our findings.  ...  in the last two editions was not included this year because of technical difficulties. tions of the TREC QA track; we followed [16] in our training procedure.  ... 
dblp:conf/trec/AhnAJMRS05 fatcat:vg2njg3w4rhjlgxsfgspyzog7e

Modeling of the Question Answering Task in the YodaQA System [chapter]

Petr Baudiš, Jan Šedivý
2015 Lecture Notes in Computer Science  
To ease performance comparisons of general-purpose QA systems, we also propose an effort in building a new reference QA testing corpus which is a curated and extended version of the TREC corpus.  ...  We briefly survey the current state of art in the field of Question Answering and present the YodaQA system, an open source framework for this task and a baseline pipeline with reasonable performance.  ...  Perhaps the most popular datasets are the TREC QA track, QALD [15] and WebQuestions [2] .  ... 
doi:10.1007/978-3-319-24027-5_20 fatcat:u7kf2bjdjfb2jmtufyzag5g7ly

Ranking related entities

Marc Bron, Krisztian Balog, Maarten de Rijke
2010 Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10  
We analyze the performance of a model that only uses cooccurrence statistics. While it identifies a set of related entities, it fails to rank them effectively.  ...  To address (1), we add type filtering based on category information available in Wikipedia.  ...  At the intersection of natural language processing and IR lies question answering (QA), which combines IE and IR, investigated at the TREC QA track [35] . What sets QA apart from Entity Retrieval?  ... 
doi:10.1145/1871437.1871574 dblp:conf/cikm/BronBR10 fatcat:3a3kgjmwezhxpksi7v5s2p4xl4

The Impact of Named Entity Normalization on Information Retrieval for Question Answering [chapter]

Mahboob Alam Khalid, Valentin Jijkoun, Maarten de Rijke
2008 Lecture Notes in Computer Science  
We evaluate two entity normalization methods based on Wikipedia in the context of both passage and document retrieval for question anwering.  ...  In the named entity normalization task, a system identifies a canonical unambiguous referent for names like Bush or Alabama.  ...  QA track [14] .  ... 
doi:10.1007/978-3-540-78646-7_83 fatcat:mz7klr3wmrgc5fd2j6jreqo6eq

Beyond Factoid QA: Effective Methods for Non-factoid Answer Sentence Retrieval [chapter]

Liu Yang, Qingyao Ai, Damiano Spina, Ruey-Cheng Chen, Liang Pang, W. Bruce Croft, Jiafeng Guo, Falk Scholer
2016 Lecture Notes in Computer Science  
TREC GOV2 collection.  ...  We compare learning to rank methods with multiple baseline methods including query likelihood and the state-of-the-art convolutional neural network based method, using an answer-annotated version of the  ...  Any opinions, findings and conclusions expressed in this material are those of the authors and do not necessarily reflect those of the sponsor.  ... 
doi:10.1007/978-3-319-30671-1_9 fatcat:asb4l5sdfbgclkdnmto76knmcq

WikiPassageQA: A Benchmark Collection for Research on Non-factoid Answer Passage Retrieval [article]

Daniel Cohen, Liu Yang, W. Bruce Croft
2018 arXiv   pre-print
The experimental results demonstrate the unique challenges presented by answer passage retrieval within topically relevant documents for future research.  ...  of state of the art neural architectures and retrieval models.  ...  Any opinions, findings and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect those of the sponsor.  ... 
arXiv:1805.03797v1 fatcat:q3a6yszqbnc7tgtjbtr6nrgvnq

Related entity finding by unified probabilistic models

Yi Fang, Luo Si
2013 World wide web (Bussum)  
TREC launched an Entity Track in 2009 to investigate the task of related entity finding.  ...  A comprehensive set of experiments were conducted on the TREC Entity Track testbeds from 2009 to 2011 with careful design to show the contributions of individual components.  ...  Another closely related area is Question answering (QA) which was investigated at the TREC QA track [47] . A comprehensive survey on QA can be found in [37] .  ... 
doi:10.1007/s11280-013-0267-8 fatcat:7ntu243m3jacfkj6nrzs4ykpre

A domain-independent approach to finding related entities

Olga Vechtomova, Stephen E. Robertson
2012 Information Processing & Management  
The evaluation was conducted on the Related Entity Finding task of the Entity Track of TREC 2010, as well as the QA list questions from TREC 2005 and 2006.  ...  An initial list of candidate entities, extracted from top ranked documents retrieved for the query, is refined using a number of statistical and linguistic methods.  ...  The approach was evaluated using the Entity track dataset of TREC 2010, as well as the QA track list questions from TREC 2005 and 2006.  ... 
doi:10.1016/j.ipm.2011.12.003 fatcat:f7hxlt36e5gw3henruj2ybyuyy

Automated Question Answering System for Community-Based Questions

Chanin Pithyaachariyakul, Anagha Kulkarni
Empirical evaluation of our system using multiple datasets demonstrates that our system outperforms the best system from the TREC LiveQA tracks, while keeping the response time to under less than half  ...  We present our attempt at developing an efficient Question Answering system for both factoid and non-factoid questions from any domain.  ...  We used the TREC LiveQA datasets to train the model.  ... 
doi:10.1609/aaai.v32i1.12159 fatcat:5spijmsxrrabdenqin4zsljmha

Barbara Made the News

Flavio Martins, João Magalhes, Jamie Callan
2016 Proceedings of the Ninth ACM International Conference on Web Search and Data Mining - WSDM '16  
Evaluation on the TREC 2013 and 2014 Microblog track datasets demonstrates that the proposed model achieves a relative improvement of 13.2% over lexical retrieval models and 6.2% over a learning to rank  ...  This allows us to predict the temporal relevance of documents for query q.  ...  TREC datasets. The experiments were performed with the Tweets2013 corpus using the query topics of the TREC 2013 and TREC 2014 editions of the Microblog track.  ... 
doi:10.1145/2835776.2835825 dblp:conf/wsdm/MartinsMC16 fatcat:slaftrg6ezap5ptmnonfxjvwa4

Overview of the Medical Question Answering Task at TREC 2017 LiveQA

Asma Ben Abacha, Eugene Agichtein, Yuval Pinter, Dina Demner-Fushman
2017 Text Retrieval Conference  
We present an overview of the medical question answering task organized at the TREC 2017 LiveQA track. The task addresses the automatic answering of consumer health questions received by the U.S.  ...  The training datasets were both from the open domain and the medical domain. We discuss the obtained results and give some insights for future research in medical question answering.  ...  Acknowledgements We would like to thank Sonya Shooshan for her help with the reference answers and NIST Assessors for judging participants' answers.  ... 
dblp:conf/trec/AbachaAPD17 fatcat:44j4ml5chrdqnfajnk2673kfdq

TongKey at Entity Track TREC 2011: Related Entity Finding

Zhengcai Pan, Haiguang Chen
2011 Text Retrieval Conference  
This paper presents our work done for the TREC 2011 Entity track. A retrieval model was proposed for the task of related entity finding.  ...  Therefore, a specific classifier trained by employing Wikipedia titles and category was utilized to identify the categories of target entities.  ...  INTRODUCTION In entity track of TREC 2011, the main task of the Related Entity Finding (REF) task is elaborated as follows: Given an input entity, by its name and homepage, the type of the target entity  ... 
dblp:conf/trec/PanC11 fatcat:vinkc4kn7baqvhvyhxbnlnqw54
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