Query Expansion through Weighted Word Pairs.

We demonstrate improvements in retrieval effectiveness in terms of increased mean average precision (MAP) garnered by the proposed linguistic-based query expansion framework through experimentation on ... Lastly, a robust weighting scheme that duly emphasizes the importance of query constituents based on their linguistic role within the expanded query is presented. ... We then extract potential expansion concepts through a proximity-based statistical query expansion method that capitalizes on grammatically linked base pairs of query concepts. ...

doi:10.1016/j.ipm.2015.04.002 fatcat:przkgga3hfg3hhp2cnrwfimswu

Multiple Versions

Our method makes use of a minimal relevance feedback to expand the initial query with a structured representation composed of weighted pairs of words. ... Such a structure is obtained from the relevance feedback through a method for pairs of words selection based on the Probabilistic Topic Model. ... ., 2002) since they handle complex query expansions through custom boolean weighted models. ...

doi:10.1016/j.ipm.2014.07.004 fatcat:xba7rgqoxzg4bckbjat3yvnrma

Specifically, we are interested in query construction that uses words, sentences, and entire passages to expand initial topic specifications in an attempt to cover their various angles, aspects and contexts ... In this paper we discuss both manual and automatic procedures for query expansion within a new stream-based information retrieval model. 299 Report Documentation Page Form Approved OMB No. 0704-0188 Public ... We acknowledge the following members of our TREC-5 team who participated in the query expansion experiments: Louise Guthrie, Jussi Karlgren, Jim Leistensnider, Troy Straszheim, and Jon Wilding. ...

doi:10.3115/974557.974601 dblp:conf/anlp/StrzalkowskiLCW97 fatcat:a4koccfixnde5ov3z6b7zz5o4q

We then introduce an artificial neural network classifier to predict the usefulness of query expansion terms. This classifier uses term word embeddings as inputs. ... Query expansion is a method for alleviating the vocabulary mismatch problem present in information retrieval tasks. ... Modeling the Query and Candidate Expansion Term Relation Given a query q and a candidate expansion term x, the model connects them as a sequence, then maps the words to their embeddings through a shared ...

arXiv:1811.03514v1 fatcat:nu2iw4u6frcepnvmsum4oahiwy

neural networks to capture expanding relations in the words embeddings' space.We afterwards started a quantitative and qualitative analysis of the weights learned by our network. ... We tried to fill this gap in the literature with a custom Query Expansion system trained and tested on open datasets. ... The expansions are therefore learned through the examples, and the models fails to enrich queries on topics it did not witness before (45% of the queries are not expanded since no new word is added). • ...

doi:10.1609/aaai.v33i01.330110075 fatcat:3duev5xhunf55b7jjpaj3zpxkq

We propose a probabilistic model for query reformulation on click-through data, which can help user auto-complete their search need. ... In the experiment, we try to reduce query drift and noise in click-through data by using crowd-sourced relevance feedback and smoothing methods. ... Recently, word embedding [7] , [13] - [15] is also used to query expansion, selecting similar words of query terms as expansion keywords. ...

doi:10.18178/ijmlc.2019.9.3.799 fatcat:3rfnnsusp5eo5cygrd27o5siee

The source of the query expansion information is the concept network knowledge base. ... Query expansion has been extensively studied as a technique for increasing information retrieval performance. ... Through query expansion, the effects of the word mismatch problem are reduced, resulting in a higher ratio of relevant documents in the retrieval results (precision) and a higher ratio of the relevant ...

doi:10.1007/11495772_30 fatcat:aop2joz5jjbrdg36lyo553uqcy

Under the Tipster contracts in phases I through III, GE group has set out to explore this potential through development and evaluation of new text processing techniques. ... Where can we get the right queries? In today's information retrieval, query expansion usually is typically limited to adding, deleting or re-weighting of terms. ... In routing, where queries are extensively tuned through training, having multiple word forms allows, in theory at least, finer~grained adjustments. ...

doi:10.3115/1119089.1119114 dblp:conf/tipster/StrzalkowskiSW98 fatcat:2n6coiubprhfzb5znakjysvucu

We tried to fill this gap in the literature with a custom Query Expansion engine trained and tested on open datasets. ... Starting from open datasets, we built a Query Expansion training set using sentence-embeddings-based Keyword Extraction. ... The expansions are therefore learned through the examples, and the models fails to enrich queries on topics it did not witness before (45% of the queries are not expanded since no new word is added). ...

arXiv:1812.10119v1 fatcat:eobr7pts2jbq5g3f6vygw6ltvy

Text search is performed via queries of words or fully qualified sentences, and results are returned in the form of ranked video clips. ... Our approach involves a query expansion stage, in which query terms are compared to the visual concepts for which we independently build classifier models. ... This allows us to compute more general semantic relatedness scores between pairs of words or phrases, which are better suited for query expansion purposes. ...

doi:10.1109/icme.2006.262892 dblp:conf/icmcs/HauboldNN06 fatcat:mrp3anzatjg4lnr7zy6dgvztja

concept weighting. ... We present here a query expansion framework which capitalizes on both linguistic characteristics of user queries and ontology resources for query constituent encoding, expansion concept extraction and ... This then translates into meaningful query concept pairing for expansion. ...

arXiv:2004.11083v1 fatcat:pxro5fus6zhrxiw32a2xbzsiue

query words. ... Then query expansion was adopted with the translation model and term-subject co-occurrence. ... From the result, it was found that the inclusion rate of existing translation strings in the translation result had been improved largely through the use of query expansion techniques. ...

doi:10.14257/ijdta.2016.9.1.13 fatcat:jtvim7dubvaehpieecm4ezqeru

The new method expands the initial query with a structured representation made of weighted word pairs (WWP) extracted from a set of training documents (relevance feedback). ... Standard text retrieval systems can handle a WWP structure through custom Boolean weighted models. ... We have chosen Apache Lucene, Indri (Lemur Project), Terrier, and Zettair because they handle complex query expansions through custom Boolean weighted models. ...

doi:10.1002/asi.23331 fatcat:x6nwikmtobb6vnq2gmwiwjkzcy

In routing, where queries are extensively tuned through training, having multiple word forms allows, in theory at least, finer-grained adjustments. ... Content-term expansion − Adding, deleting or re-weighting of terms − Content terms from documents judged relevant are added to the query − Weights of all terms are adjusted in order to reflect the relevance ...

doi:10.1007/978-94-017-2388-6_5 fatcat:aghtqm4pzvahdkscj2srnetxaa

QECK identifies software-specific expansion words from the high quality pseudo relevance feedback question and answer pairs on Stack Overflow to automatically generate the expansion queries. ... By reformulating the queries, query expansion provides effective ways to solve the term mismatch problem. ... After weighting the words, top-n words can be identified as expansion words. ...

doi:10.1109/tsc.2016.2560165 fatcat:5cae7b5okvdxdixmjwncqrgdiy

Multiple Versions

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