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Improved open-vocabulary spoken content retrieval with word and subword lattices using acoustic feature similarity : Spoken Content RetrievalLEE, Hung-yi; CHOU, Po-wei; LEE, Lin-shan et al.Computer speech & language (Print). 2014, Vol 28, Num 5, pp 1045-1065, issn 0885-2308, 21 p.Article

Collaborative pseudo-relevance feedbackDONG ZHOU; TRURAN, Mark; JIANXUN LIU et al.Expert systems with applications. 2013, Vol 40, Num 17, pp 6805-6812, issn 0957-4174, 8 p.Article

Swapping documents and termsCLARKE, Charles L. A; CORMACK, Gordon V; LYNAM, Thomas R et al.Information retrieval (Boston). 2009, Vol 12, Num 6, pp 680-694, issn 1386-4564, 15 p.Conference Paper

On the number of terms used in automatic query expansionOGILVIE, Paul; VOORHEES, Ellen; CALLAN, Jamie et al.Information retrieval (Boston). 2009, Vol 12, Num 6, pp 666-679, issn 1386-4564, 14 p.Conference Paper

Improving pseudo relevance feedback based query expansion using genetic fuzzy approach and semantic similarity notionBHATNAGAR, Pragati; PAREEK, Narendra.Journal of information science. 2014, Vol 40, Num 4, pp 523-537, issn 0165-5515, 15 p.Article

Weighted Word Pairs for query expansionCOLACE, Francesco; DE SANTO, Massimo; GRECO, Luca et al.Information processing & management. 2015, Vol 51, Num 1, pp 179-193, issn 0306-4573, 15 p.Article

A deterministic resampling method using overlapping document clusters for pseudo-relevance feedbackKYUNG SOON LEE; CROFT, W. Bruce.Information processing & management. 2013, Vol 49, Num 4, pp 792-806, issn 0306-4573, 15 p.Article

Exploring criteria for successful query expansion in the genomic domainSTOKES, Nicola; YI LI; CAVEDON, Lawrence et al.Information retrieval (Boston). 2009, Vol 12, Num 1, pp 17-50, issn 1386-4564, 34 p.Article

Does pseudo-relevance feedback improve distributed information retrieval systems?MARTINEZ-SANTIAGO, Fernando; GARCIA-CUMBRERAS, Miguel A; URENA-LOPEZ, L. Alfonso et al.Information processing & management. 2006, Vol 42, Num 5, pp 1151-1162, issn 0306-4573, 12 p.Article

A syntactically-based query reformulation technique for information retrievalLIOMA, C; OUNIS, I.Information processing & management. 2008, Vol 44, Num 1, pp 143-162, issn 0306-4573, 20 p.Article

Combining fields for query expansion and adaptive query expansionBEN HE; OUNIS, Iadh.Information processing & management. 2007, Vol 43, Num 5, pp 1294-1307, issn 0306-4573, 14 p.Article

A merging strategy proposal : The 2-step retrieval status value methodMARTINEZ-SANTIAGO, Fernando; URENA-LOPEZ, L. Alfonso; MARTIN-VALDIVIA, Maite et al.Information retrieval (Boston). 2006, Vol 9, Num 1, pp 71-93, issn 1386-4564, 23 p.Article

Term disambiguation techniques based on target document collection for cross-language information retrieval : An empirical comparison of performance between techniquesKISHIDA, Kazuaki.Information processing & management. 2007, Vol 43, Num 1, pp 103-120, issn 0306-4573, 18 p.Article

Information retrieval with concept-based pseudo-relevance feedback in MEDLINEJALALI, Vahid; MOHAMMAD REZA MATASH BORUJERDI.Knowledge and information systems (Print). 2011, Vol 29, Num 1, pp 237-248, issn 0219-1377, 12 p.Article

Enhancing Query Formulation for Spoken Document Retrieval : EMERGING TECHNOLOGIES AND APPLICATIONS OF ARTIFICIAL INTELLIGENCECHEN, Berlin; CHEN, Yi-Wen; CHEN, Kuan-Yu et al.Journal of information science and engineering. 2014, Vol 30, Num 3, pp 553-569, issn 1016-2364, 17 p.Article

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