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A term dependency-based approach for query terms ranking

Chia-Jung Lee, Ruey-Cheng Chen, Shao-Hang Kao, Pu-Jen Cheng
2009 Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09  
In this paper, we propose an approach to rank a set of given query terms according their effectiveness, wherein top ranked terms will be selected as an effective query.  ...  Our ranking approach exploits and benefits from the underlying relationship between the query terms, and thereby the effective terms can be properly combined into the query.  ...  In the rest of this paper, we first make a brief review on related work in Section 2, and describe our term dependency-based approach for query terms ranking in Section 3.  ... 
doi:10.1145/1645953.1646114 dblp:conf/cikm/LeeCKC09 fatcat:2jjy34icxne2td5qfdpfyrbzdq

Query term ranking based on dependency parsing of verbose queries

Jae Hyun Park, W. Bruce Croft
2010 Proceeding of the 33rd international ACM SIGIR conference on Research and development in information retrieval - SIGIR '10  
Query term ranking approaches are used to select effective terms from a verbose query by ranking terms.  ...  We also modify the method for measuring the effectiveness of query terms for query term ranking.  ...  A previous approach [6] ranks sets of terms in order to take account of underlying relations between terms. This approach increases a query term weighting list and causes a data sparseness problem.  ... 
doi:10.1145/1835449.1835637 dblp:conf/sigir/ParkC10 fatcat:z6q5lpwhqrfztfjbg6wc7durcy

Relevance Ranking Using Kernels [chapter]

Jun Xu, Hang Li, Chaoliang Zhong
2010 Lecture Notes in Computer Science  
In the approach, the general ranking model is defined as a kernel function of query and document representations.  ...  This paper is concerned with relevance ranking in search, particularly that using term dependency information.  ...  Model Construction Let us introduce the way of creating a kernel-based ranking model. We first identify a 'type of dependent query terms' for which we care about the occurrences in documents.  ... 
doi:10.1007/978-3-642-17187-1_1 fatcat:xvvinwajx5aq5f5prdxc7wcsai

Leveraging Temporal Query-Term Dependency for Time-Aware Information Access

Bilel Moulahi, Lynda Tamine, Sadok Ben Yahia
2015 2015 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)  
Moreover, we reframe the task as a rank aggregation problem that fully exploits the temporal features of query terms.  ...  In this paper, we observe through a time series analysis that, query terms are temporally dependent and are frequently occurring within similar time periods when they deal with the same topics.  ...  Return Document ranking of query q 1) Generating the Query-Terms Rankings: Our approach relies on the time-based model proposed in [4] , based in turn on a temporal probabilistic model from [8] .  ... 
doi:10.1109/wi-iat.2015.128 dblp:conf/webi/MoulahiTY15 fatcat:dlpll6tj7zfglifhib7ejrbkku

Semantic concept-enriched dependence model for medical information retrieval

Sungbin Choi, Jinwook Choi, Sooyoung Yoo, Heechun Kim, Youngho Lee
2014 Journal of Biomedical Informatics  
In this study, we incorporate a semantic concept-based termdependence feature into a formal retrieval model to improve its ranking performance.  ...  These semantic concept-based dependence features were incorporated into a semantic concept-enriched dependence model (SCDM).  ...  In a statistical language modeling approach, query q is assumed to be generated by a probabilistic model based on document d. Thus, the documents are ranked according to the query likelihood, p(q|d).  ... 
doi:10.1016/j.jbi.2013.08.013 pmid:24036003 fatcat:e2dll5bvjbbazkcggar64zwhdu

Term associations in query expansion

Michael Symonds, Guido Zuccon, Bevan Koopman, Peter Bruza, Laurianne Sitbon
2013 Proceedings of the 22nd ACM international conference on Conference on information & knowledge management - CIKM '13  
State-of-the-art dependency-based approaches primarily model term associations known within structural linguistics as syntagmatic associations, which are formed when terms co-occur together more often  ...  Many successful query expansion techniques ignore information about the term dependencies that exist within natural language.  ...  INTRODUCTION Dependency-based models of information retrieval have demonstrated superior retrieval effectiveness over models that ignore term dependencies, like tf.idf and language modelling approaches  ... 
doi:10.1145/2505515.2507852 dblp:conf/cikm/SymondsZKBS13 fatcat:nbnxylefzrgk5mlbhpgtqakfgy

Exploration of query context for information retrieval

Keke Cai, Chun Chen, Jiajun Bu, Peng Huang, Zhiming Kang
2007 Proceedings of the 16th international conference on World Wide Web - WWW '07  
The experiments show that the proposed contextbased approach for information retrieval can greatly improved relevance of search results.  ...  In this paper we interpret query context as a document consisting of sentences related to the current query.  ...  EXPERIMENTS CONCLUSIONS AND FUTURE WORK We propose a novel context-based retrieval approach for document re-ranking.  ... 
doi:10.1145/1242572.1242743 dblp:conf/www/CaiCBHK07 fatcat:efvlca5z3bhyzpiglrahctwfoy

Comparing Approaches for Query Autocompletion

Giovanni Di Santo, Richard McCreadie, Craig Macdonald, Iadh Ounis
2015 Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval - SIGIR '15  
Hence, in this paper, we present a comparison study between current approaches to rank candidate query completions for the user query as it is typed.  ...  There are a large number of approaches to automatically rank candidate queries for the purposes of auto-completion. However, no study exists that compares these approaches on a single dataset.  ...  The score for a candidate query is the mean of the scores for its terms.  ... 
doi:10.1145/2766462.2767829 dblp:conf/sigir/SantoMMO15 fatcat:h7dsbdlalzdcvmpg5cqpb6bq3a

Improved latent concept expansion using hierarchical markov random fields

Hao Lang, Donald Metzler, Bin Wang, Jin-Tao Li
2010 Proceedings of the 19th ACM international conference on Information and knowledge management - CIKM '10  
In this paper, we propose a novel query expansion technique that models the various types of dependencies that exist between original query terms and expansion terms within a robust, unified framework.  ...  expansion approaches, including relevance-based language models and LCE.  ...  LCE is the first formalized query expansion approach that provides a mechanism for modeling term dependencies during expansion.  ... 
doi:10.1145/1871437.1871473 dblp:conf/cikm/LangMWL10 fatcat:4vmpbrypynbl5hvpdtaldvcgrm

A ranking framework for entity oriented search using Markov random fields

Hadas Raviv, David Carmel, Oren Kurland
2012 Proceedings of the 1st Joint International Workshop on Entity-Oriented and Semantic Search - JIWES '12  
In this work we present a general model for entity ranking that is based on the Markov Random Field approach for modeling various types of dependencies between the query and the entity.  ...  We show that this model actually extends existing approaches for entity ranking while aggregating all pieces of relevance evidences in a unified way.  ...  Acknowledgments We thank the anonymous reviewers for their comments.  ... 
doi:10.1145/2379307.2379308 fatcat:naaiewdnd5g3pkifryqblhdl4i

SEM13 at the NTCIR-11 IMINE Task: Subtopic Mining and Document Ranking Subtasks

Md Zia Ullah, Masaki Aono
2014 NTCIR Conference on Evaluation of Information Access Technologies  
In the Subtopic Mining subtask, we mine subtopics from query suggestions, query dimensions, and Freebase entities of a given query, rank them based on their importance for the given query, and finally  ...  For document ranking run, the best performance of our system achieves a D#-nDCG@10 of 0.6022 (coarse-grain) and 0.5291 (fine-grain), which are a comparable performance to other participants.  ...  The term dependency with Markov random field based feature, fMRF is computed from the query and the subtopic candidate.  ... 
dblp:conf/ntcir/UllahA14 fatcat:zatetaiidfc4vchumb3ycbva5u

An initial attempt to improve spoken term detection by learning optimal weights for different indexing features

Yu-Hui Chen, Chia-Chen Chou, Hung-Yi Lee, Lin-shan Lee
2010 2010 IEEE International Conference on Acoustics, Speech and Signal Processing  
These weights can be learned by optimizing a desired spoken term detection performance measure over a training document set and a training query set.  ...  In this paper, we present an initial attempt of using two weighting schemes, one context independent (fixed weight for each feature) and one context dependent(different weights for the same feature in  ...  PROPOSED APPROACH 2: CONTEXT DEPENDENT WEIGHTING The above weighting scheme assumes all terms have a fixed weight, but in fact the importance of a term in retrieval may depend on the context.  ... 
doi:10.1109/icassp.2010.5494981 dblp:conf/icassp/ChenCLL10 fatcat:q6hio72infa27jy7jrzog5gvee

Query Transformations for Result Merging

Shriphani Palakodety, Jamie Callan
2014 Text Retrieval Conference  
In this document, we explore how term-dependence models and query expansion strategies influence result-merging.  ...  Approaches from previous attempts at solving this problem involved custom querydocument similarity scores or rank-combination methods.  ...  In both approaches, the terms retrieved for a query are similar to a vector (which represents terms or a query aggregate).  ... 
dblp:conf/trec/PalakodetyC14 fatcat:pvsglhoxmbd7dcglditgtja54a

Enhancing query reformulation by combinig content and hypertext analyses

Anis Benammar
2004 European Conference on Information Systems  
In a second step, a co-occurrence analysis is performed on the local document set to deduce the terms to be used for the query expansion.  ...  To build the local set we use firstly a content-based analysis. It is a similarity study between the retrieved documents and the query.  ...  Query expansion methods consist in adding new terms to the initial query. These approaches can be grouped in three categories: • User relevance feedback approaches: they are based on user feedback.  ... 
dblp:conf/ecis/Benammar04 fatcat:2jdecjlluzdm7p6pob7rnddvcq

USC/ISI at TREC 2011: Microblog Track

Donald Metzler, Congxing Cai
2011 Text Retrieval Conference  
, and a feature-based ranking model that uses a simple, but effective learningto-rank model.  ...  Our system makes use of best-practice ranking techniques, including term, phrase, and proximity-based text matching via the Markov random field model, pseudo-relevance feedback using Latent Concept Expansion  ...  We would also like to thank the volunteers that helped us construct a small set of training data.  ... 
dblp:conf/trec/MetzlerC11 fatcat:t2dgxf366ffthdlemuh236wo2a
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