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Latent semantic indexing model for Boolean query formulation (poster session)

Dae-Ho Baek, HeuiSeok Lim, Hae-Chang Rim
2000 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '00  
A new model named Boolean Latent Semantic Indexing model based on the Singular Value Decomposition and Boolean query formulation is introduced.  ...  Retrieval experiments on a number of test collections seem to show that the proposed model achieves substantial performance gains over the Latent Semantic Indexing model.  ...  The Latent Semantic Indexing (LSI) tries to overcome the problems of lexical matching by using statistically derived conceptual indices instead of individual words for retrieval.  ... 
doi:10.1145/345508.345612 dblp:conf/sigir/BaekLR00 fatcat:ugiuwi4zrjco3ps3hwnvbt3dhi

An Information-Theoretic Approach for Unsupervised Topic Mining in Large Text Collections

Eduardo H. Ramirez, Ramon F. Brena
2009 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology  
In contrast to probabilistic topic modeling methods that require rst estimating the density of probability distributions, we model topics as subsets of terms that are used as queries to an index of documents  ...  By retrieving the documents relevant to those topical-queries we obtain overlapping clusters of semantically similar documents.  ...  Later, Hofmann [4] proposed a probabilistic version of LSI, namely Probabilistic Latent Semantic Indexing (PLSI).  ... 
doi:10.1109/wi-iat.2009.58 dblp:conf/webi/RamirezB09 fatcat:l3ovtxvxp5elhg4jusox5dpz6i

A Literature Review on Patent Information Retrieval Techniques

Alok Khode, Sagar Jambhorkar
2017 Indian Journal of Science and Technology  
Objective: Patents are critical intellectual assets for any competitive business. They can prove to be a gold mine if retrieved, analyzed and utilized appropriately.  ...  Application/Improvement: Considering the various techniques and frameworks available and their limitations, there is a lot of scope in the field of patent retrieval techniques which makes room for further  ...  Models: Vector space model(VSM), semantic based processing, latent semantic analysis(LSA), language model, weighting techniques, probabilistic model etc.  ... 
doi:10.17485/ijst/2017/v10i37/116435 fatcat:sux6dzrm3re7dig44xrpl7agya

A Survey of Information Retrieval Models for Malayalam Language Processing

Arjun Babu, Sindhu L.
2014 International Journal of Computer Applications  
General Terms Information Retrieval (IR), Malayalam, IR Models Keywords Boolean Model, vector space Model, Probabilistic Model, Bayesian network Model, Inference Network Model, Latent  ...  There are several Information Retrieval models developed for efficient document retrieval. In this survey paper we describe major IR models which are used for various document retrieval purposes.  ...  model and Alternative Algebraic model describes latent semantic indexing and Neural network model.  ... 
doi:10.5120/18820-0230 fatcat:tm37gfyvrvbtfhyzzybow225bq

A Taxonomy of Information Retrieval Models and Tools

Gerardo Canfora, Luigi Cerulo
2004 Journal of Computing and Information Technology  
This paper proposes a taxonomy of information retrieval models and tools and provides precise definitions for the key terms.  ...  The aim is to provide a framework for classifying existing information retrieval models and tools and a solid point to assess future developments in the field.  ...  Latent semantic.  ... 
doi:10.2498/cit.2004.03.01 fatcat:psuycqgkr5aglkwmlkddaegkwe

Online Matrix Factorization for Multimodal Image Retrieval [chapter]

Juan C. Caicedo, Fabio A. González
2012 Lecture Notes in Computer Science  
In this paper, we propose a method to build an index for image search using multimodal information, that is, using visual features and text data simultaneously.  ...  The method combines both data sources and generates one multimodal representation using latent factor analysis and matrix factorization.  ...  semantic meanings for users observing them.  ... 
doi:10.1007/978-3-642-33275-3_42 fatcat:d3h2huf36bbjtnxvkxgxaawayq

Classical and Probabilistic Information Retrieval Techniques: An Audit

Qaiser Abbas
2021 Lahore Garrison University research journal of computer science and information technology  
The most important information retrieval methods include the probabilistic, fuzzy set, vector space, and boolean models.  ...  The incredible increase in information resources on the Internet formulates the information retrieval procedure, a monotonous and complicated task for users.  ...  case Generalized Belief based, Fuzzy vector network set, Latent semantic indexing, the BIR model, we need to measure the likelihood for a given document as in most other possibly IR models.  ... 
doi:10.54692/lgurjcsit.2021.0503221 fatcat:z5becjxpdvdzhabyixmx6pfjl4

Remedies against the Vocabulary Gap in Information Retrieval [article]

Christophe Van Gysel
2017 arXiv   pre-print
More specifically, we propose (1) methods to formulate an effective query from complex textual structures and (2) latent vector space models that circumvent the vocabulary gap in information retrieval.  ...  While term-based approaches are intuitive and effective in practice, they are based on the hypothesis that documents that exactly contain the query terms are highly relevant regardless of query semantics  ...  Consequently, our findings may change when considering other retrieval model classes, such as boolean models or semantic matching models.  ... 
arXiv:1711.06004v1 fatcat:6vkhvfby3zbzrepgopunm7gie4

Indexing by latent semantic analysis

Scott Deerwester, Susan T. Dumais, George W. Furnas, Thomas K. Landauer, Richard Harshman
1990 Journal of the American Society for Information Science  
A new method for automatic indexing and retrieval is described.  ...  of terms found in queries.  ...  We thank Mike Lesk for advice and comments on previous drafts of the paper, and Ram Gnanadesikan, John Kettenring and John Tukey for consultation on statistical questions.  ... 
doi:10.1002/(sici)1097-4571(199009)41:6<391::aid-asi1>3.0.co;2-9 fatcat:pn4mahimjbb4hayvq6ynql3g3i

An Algorithm for Semantic Expansion of Queries in a Boolean Information Retrieval System

Ana Laura Lezama, Mireya Tovar, David Pinto, Darnes Vilariño
2016 Research in Computing Science  
In this paper, we propose an algorithm for query expansion of a Boolean Information Retrieval System (BIRS), in which the queries are formed by the concepts of four domain ontologies.  ...  initial query is sought within a set of a domain documents chosen by the user.  ...  This research work has been partially supported by Sectoral Research Fund for Education CONACyT project 257357, VIEP-BUAP project 00570 and PRODEP-SEP project 00570 (EXB-792) DSA/103.5/15/10854.  ... 
doi:10.13053/rcs-130-1-6 fatcat:3tk6qh54i5agdafj7bvk3ovbdq

A Generalized Framework for Ontology-Based Information Retrieval Application to a public-transportation system [article]

Amir Zidi, Mourad Abed
2014 arXiv   pre-print
In order to achieve more scalability, we propose an approach for semantic indexing based on entity retrieval model.  ...  In this paper we present a generic framework for ontology-based information retrieval.  ...  Semantic Indexing As our knowledge base is constituted of entities defined for RDF, RDFs and OWL, we designed an indexing system using entity retrieval model. 1) Entity retrieval model A knowledge base  ... 
arXiv:1409.0921v1 fatcat:ggshzpypkbhbvlt33owoyv23py

N-layer Approach to Web Information Retrieval

Jayant Gadge, S.S. Sane, H.B. Kekre
2013 International Journal of Applied Information Systems  
In web information retrieval, the terms or keywords are used for indexing purpose of document.  ...  Vector space model ignores the importance of these terms with respect to their position while calculating the weight of the indexing terms.  ...  There are several representations such as Boolean Retrieval model, Fuzzy Set model, Extended Boolean model, Vector Space model, Latent Semantic indexing model.  ... 
doi:10.5120/ijais12-450840 fatcat:ssj5j5jlcvbrpozfb6yuv4cnvy

Page 58 of Library & Information Science Abstracts Vol. , Issue 7 [page]

1995 Library & Information Science Abstracts  
Latent Semantic Indexing (LSI) and MatchPlus are 2 attempts to model and exploit the inter relationships LIBRARY & INFORMATION SCIENCE ABSTRACTS REFSESSEE | RE a) SERRCSES SEG ELSES SEF E seeserssoy.._  ...  Reasons for the failure of postcoordinate searches include the absence of specified relationships between terms, the complexity of formulating Boolean searches, and the high frequency of terms in large  ... 

A coherent query language for XML

Krishnaprasad Thirunarayan, Trivikram Immaneni
2008 Journal of Intelligent Information Systems  
Text search engines are inadequate for indexing and searching XML documents because they ignore metadata and aggregation structure implicit in the XML documents.  ...  In this paper, we present a simple yet flexible query language, and develop its semantics to enable intuitively appealing extraction of relevant fragments of information while simultaneously falling back  ...  Acknowledgements: We thank the referees for their valuable feedback.  ... 
doi:10.1007/s10844-007-0051-2 fatcat:t5joiiho75gd5anr754vlvr3aq

Concept Based Representations as Complement of Bag of Words in Information Retrieval [chapter]

Maya Carrillo, Aurelio López-López
2010 IFIP Advances in Information and Communication Technology  
In this paper we use random indexing, which uses co-occurrence information among words to generate semantic context vectors and then represent the documents and queries as BoC.  ...  Information Retrieval models, which do not represent texts merely as collections of the words they contain, but rather as collections of the concepts they contain through synonym sets or latent dimensions  ...  There is research that has sought to include such semantic aspects as Latent Semantic Analysis [9] , which has included implicit context information in the indexing process.  ... 
doi:10.1007/978-3-642-16239-8_22 fatcat:ib5d7p5wvrawblx5ryakzd2oc4
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