01110nas a2200145   4500008004100000245009500041210006900136260001200205300001200217490000700229520061800236100003100854700002300885856005600908       2020                        eng d00aQuery Expansion in Text Information Retrieval with Local Context and Distributional Model-0 aQuery Expansion in Text Information Retrieval with Local Context  c12/2019  a313-3200 v173 a<p>The Semantic Distributional Model is based on the frequency of contexts of use of language terms in large open corpus such as the web, to establish similarity or the relationship between words. These relationships or similarities can be used to add terms when expanding queries. The idea explored in this paper is that, for queries in closed collections of text documents, a posterior filter based on the restricted vocabulary of the collection can improve the effectiveness of automatic query expansion. This idea is developed and evaluated in publicly available benchmarks presenting promising results.</p>
1 ada Silva, Fabiano, Tavares1 aMaia, José, E. B.  uhttp://dline.info/fpaper/jdim/v17i6/jdimv17i6_1.pdf01567nas a2200145   4500008004100000245014000041210006900181260001200250300001000262490000700272520104400279100002401323700001801347856005601365       2018                        eng d00aQuery Expansion with Enhanced-BM25 Approach for Improving the Search Query Performance on Clustered Biomedical Literature Retrieval –0 aQuery Expansion with EnhancedBM25 Approach for Improving the Sea  c04/2018  a86-980 v163 a<p>The aim of this paper is to improve the search query performance of the biomedical literature by expanding the queries with most significant terms. Methods: In this article, an enhanced BM25 mathematical approach is proposed to retrieve the most query relevant literature from clustered Biomedical literature bank with query expansion from MeSH. The clustered biomedical topics are analyzed with different pre-processing methods and term-weighting functions and found the best values for the tuning parameters K1, b, K3 and the right combination of pre-processing and term weighting functions for improving the query performance in terms of Average Precision, Mean Average Precision and R-precision. Novelty/Improvements: In this approach, the existing best match retrieval technique is normalized with the calibrate constants K1 = 1.3, b = 0.75, K3 = 1.2 and the significant terms are identified with comparison of MeSH for query expansion. The retrieval performance is improved in terms of Mean Average Precision and R-precision</p>
1 aMD, ThayyabaKhatoon1 aGovardhan, A.  uhttp://dline.info/fpaper/jdim/v16i2/jdimv16i2_4.pdf00488nas a2200133   4500008004100000245013600041210006900177260001200246300001000258490000700268100002400275700001800299856003700317       2018                        eng d00aQuery Expansion with Enhanced-BM25 Approach for Improving the Search Query Performance on Clustered Biomedical Literature Retrieval0 aQuery Expansion with EnhancedBM25 Approach for Improving the Sea  c04/2018  a85-980 v161 aMD, ThayyabaKhatoon1 aGovardhan, A.  uhttps://dline.info/newl/node/65400464nas a2200145   4500008004100000245009400041210006900135260001200204300001200216490000700228100002600235700000500261700001500266856003700281       2018                        eng d00aQuery Optimization on Distributed Health Database DBD by Minimizing Attribute Involvement0 aQuery Optimization on Distributed Health Database DBD by Minimiz  c06/2018  a105-1130 v161 aN, Slamet, Sudaryanto1 a1 aS, Maryani  uhttps://dline.info/newl/node/67501363nas a2200193   4500008004100000245006200041210006200103260000900165300001400174490000600188520076700194653002100961653002100982653001901003653000801022100001101030700001101041856011701052       2011                        eng d00aQuerying and ranking xml documents based on data synopses0 aQuerying and ranking xml documents based on data synopses  c2011  a199 - 2050 v93 aThere is an increasing interest in recent years for querying and ranking XML documents. In this paper, we present a new framework for querying and ranking schema-less XML documents based on concise summaries of their structural and textual content. We introduce a novel data synopsis structure to summarize the textual content of an XML document for efficient indexing. More importantly, we extend the traditional vector space model to effectively rank XML documents over the proposed data synopses. We conduct extensive experiments over XML benchmark data to demonstrate the advantages of the indexing scheme and the effectiveness of our ranking scheme. We also compare our framework with Lucene to demonstrate our extended TF*IDF scoring function is effective.10aDocument ranking10aQuery processing10aQuery synopses10aXML1 aHe, W.1 aLv, T.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-84855362331&partnerID=40&md5=85a8a3de60a877da1d0a3495eaf27e2201854nas a2200205   4500008004100000245008300041210006900124260000900193300001400202490000600216520115100222653002401373653002901397653002301426653002801449653001301477100001801490700002301508856011701531       2010                        eng d00aQos-aware selection of web service compositions using Harmony Search algorithm0 aQosaware selection of web service compositions using Harmony Sea  c2010  a160 - 1660 v83 aExtensive use of web services has lead to introduce web service compositions to execute business workfiows. Since several function equivalent services, provided by different service providers, may be available in the Web, the problem of selection of web service compositions arises. QoS aware selection means considering the quality of the service composition in choosing constituent services. So a method is needed for computing the quality of a composition and determining the composition with the (almost) best quality. The resulting composite has optimal quality and satisfies user's quality constraints. In this paper, the problem of QoS aware selection of web service composition is modeled as an optimization problem. Then a variation of Harmony Search algorithm is used to find a near optimal composition. Harmony Search is a recently developed optimization algorithm that mimics the improvisation process. The proposed method based on Harmony Search has been applied to a large variety of composition schemas, generated by a simulation software, and the results show that the proposed method works faster, compared with other approaches.10aGlobal optimization10aHarmony Search algorithm10aQuality-of-service10aWeb service composition10aWorkflow1 aJafarpour, N.1 aKhayyambashi, M.R.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79960212292&partnerID=40&md5=8b2aa95f15cbf2d77baea346d4870d0401726nas a2200205   4500008004100000245008200041210006900123260000900192300001400201490000600215520104000221653002801261653000801289653003701297653002201334100001501356700001501371700001701386856011701403       2010                        eng d00aA query-oriented XML fragment search approach on a relational database system0 aqueryoriented XML fragment search approach on a relational datab  c2010  a175 - 1800 v83 aIn this paper, we propose a query-oriented fragment search approach for efficient and effective XML search engines on relational database systems. Conventional approaches for XML fragment search have only considered statistics of XML documents stored in a database system to rank a search result. As a result, almost all XML fragment search engines have attained negative results in the research field of information retrieval (IR). To cope with this problem, considering not only statistics in the database system but also ones extracted from a query helps to improve retrieval accuracy of XML fragment search engines; however, it is also faced with a problem related with their efficiencies. Therefore, we have to devise ways of achieving both highly-relevant search results and efficient query processing. We implemented our XML search engine adopting the query-oriented fragment search approach, and found that it allows users to search XML fragments more accurately and effectively than conventional ones on our XML search engine.10aEfficient and effective10aRDB10aScoring method for XML fragments10aXML search engine1 aKeyaki, A.1 aHatano, K.1 aMiyazaki, J.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79956028452&partnerID=40&md5=42415d9f4c5aca4c312c791ecc719adb01313nas a2200241   4500008004100000245011000041210006900151260000900220300001200229490000600241520052700247653002700774653000800801653002000809653001900829653002400848100001400872700002000886700001700906700001600923700001500939856011700954       2009                        eng d00aA query answering surveillance system for detecting and tracking moving objects using bounding rectangles0 aquery answering surveillance system for detecting and tracking m  c2009  a15 - 200 v73 aIn many computer vision applications such as surveillance systems, detecting moving objects is the first step of information extraction. This paper introduces a query answering system that aims at responding to user queries without the need to scan the whole video tape. the proposed system is based on finding the minimum boundary rectangles (MBRs) of moving objects which appear in the video. It detects moving objects in the video frame set, keeps track of those objects, and saves information to answer future queries.10aBackground subtraction10aMBR10aObject tracking10aRgb difference10aSurveillance system1 aSleit, A.1 aAlmobaideen, W.1 aQatawneh, M.1 aBarakat, A.1 aSaadeh, H.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-70350676981&partnerID=40&md5=bf39ff54dd637a3f58625643a68ed65a01542nas a2200193   4500008004100000245006100041210005800102260000900160300001400169490000600183520091700189653002601106653002101132653002601153653002401179100001401203700001401217856011701231       2009                        eng d00aQuery-by-multiple-examples using support vector machines0 aQuerybymultipleexamples using support vector machines  c2009  a202 - 2100 v73 aWe identify and explore an Information Retrieval paradigm called Query-By-Multiple-Examples (QBME) where the information need is described not by a set of terms but by a set of documents. Intuitive ideas for QBME include using the centroid of these documents or the well-known Rocchio algorithm to construct the query vector. We consider this problem from the perspective of text classification, and find that a better query vector can be obtained through learning with Support Vector Machines (SVMs). For online queries, we show how SVMs can be learned from one-class examples in linear time. For offline queries, we show how SVMs can be learned from positive and unlabeled examples together in linear or polynomial time, optimising some meaningful multivariate performance measures. The effectiveness and efficiency of the proposed approaches have been confirmed by our experiments on four real-world datasets.10aInformation retrieval10aMachine learning10aSupportvector machine10aText classification1 aZhang, D.1 aLee, W.S.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-77953247724&partnerID=40&md5=8fea0823a5d70e478bf228f315a5ef8901359nas a2200205   4500008004100000245005300041210005300094260000900147300001400156490000600170520073400176653001400910653002600924653001700950653002100967100001700988700001301005700001801018856011701036       2008                        eng d00aQuery planning in the PORDaS P2P database system0 aQuery planning in the PORDaS P2P database system  c2008  a307 - 3140 v63 aComputational science is a rapidly growing multidisciplinary field that has a need for scalable, distributed, and efficient data management. In our research, we see the peer-to-peer (P2P) paradigm a possible solution to some of the problems in distributed data management. P2P has already proved to be suitable in contexts like file sharing, distributed computations, and distributed search. In our research we are aiming at using P2P to solve some problems in the domain of distributed databases. In this paper we 1) present PORDaS, a distributed DBMS based on P2P techniques, 2) describe query processing and query planning in PORDaS, and 3) present results from an experimental evaluation of different query planning variants.10aData grid10aDistributed databases10aPeer-to-peer10aQuery processing1 aNørvåg, K.1 aEide, E.1 aStandal, O.H.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-70349991902&partnerID=40&md5=ac29e0f628f2878d089fa8c43f3eb0de02212nas a2200193   4500008004100000245009100041210006900132260000900201300001400210490000600224520150300230653004301733653001701776653002601793653002501819653003901844100001801883856011701901       2007                        eng d00aQuerying unstructured and structured peer-to-peer networks: Models, issues, algorithms0 aQuerying unstructured and structured peertopeer networks Models   c2007  a201 - 2100 v53 aPeer-to-Peer (P2P) networks are defined as a collection of peers that expose client/server functionalities simultaneously. P2P systems, built on top of P2P networks, support information sharing primitives and lookup mechanisms of data objects located on peers. It has been demonstrated that the P2P paradigm is able to efficiently capture models and, above all, dynamics of modem applications, beyond limitations of conventional produce/consumer paradigms. Traditionally, P2P primitives and mechanisms have been implemented by means of keyword-based search and matching operations. Modern P2P systems require more complex query functionalities, beyond capabilities of DBMS-inspired models and algorithms. As a consequence, the issue of efficiently querying the underling P2P network is gaining momentum in the research community. Indeed, querying P2P networks, which can be in the unstructured and structure modes, plays a critical role in next-generation P2P systems, as its performance heavily affect the efficiency of the overall system. Starting from these considerations, in this paper we propose a survey on models, issues and algorithms for querying unstructured and structured P2P systems. We also put in evidence similarities and differences of state-of-the-art proposals appearing in literature, with critical discussion, and we provide a rigorous taxonomy of P2P query strategies. Finally, we complete our analytical contribution via hihlighting future directions in this research field.10aIssues and algorithms for P2P networks10aQuery models10aQuerying P2P networks10aRouting P2P networks10aTaxonomies of P2P query strategies1 aCuzzocrea, A.  uhttp://www.scopus.com/inward/record.url?eid=2-s2.0-44949141961&partnerID=40&md5=6ec618e515388beb0fc88c49914b8058