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An object-oriented modeling of the history of optimal retrievals

Yong Zhang, Vijay V. Raghavan, Jitender S. Deogun
1991 Proceedings of the 14th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '91  
Since obtaining relevance judgments and constructing an oplitnal query involve a great deal of effort, in this paper, we develop a framework for organizing the history of optimal retrievals. The j?  ...  amework involves the identi~cation of a hierarchy of document classes such that the concepts corresponding to higher level classes are more general than those of the lower level classes.  ...  As a result of the clustering algorithm, we discover many clusters of concepts.  ... 
doi:10.1145/122860.122885 dblp:conf/sigir/ZhangRD91 fatcat:6udoagpsqbhqlby36fhdo6a3ai

Multivariable Adaptive Optimization Based on the Structural Equation Set

2016 Revista Técnica de la Facultad de Ingeniería Universidad del Zulia  
In addition, the concept of relative generalization of two equivalence relations is defined, and applied in solving the optimization problem of the multivariable test.  ...  Through an example, the comparison is conducted on the multivariate network cluster method which is proposed in this paper and the single network variable network cluster method.  ...  The concept of the relative generalization will be applied for the optimization multivariate test.  ... 
doi:10.21311/ fatcat:aivea557qvewpdqzgu7imk4zoe

Performance evaluation and optimization for content-based image retrieval

Julia Vogel, Bernt Schiele
2006 Pattern Recognition  
Based on the model, we develop closed-form expressions that allow for the prediction as well as the optimization of the retrieval performance.  ...  Users are querying the system through image description using a set of local semantic concepts and the size of the image area to be covered by the particular concept.  ...  Acknowledgements This work was supported in part by the CogVis Project, funded by the Commission of the European Union under Grant IST-2000-29375, and the Swiss Federal Office for Education and Science  ... 
doi:10.1016/j.patcog.2005.10.024 fatcat:khchjcww7zhbpdlxu47yqhd43e

Hybrid Fuzzy-ontology Design Using FCA Based Clustering for Information Retrieval in Semantic Web

K. Balasubramaniam
2015 Procedia Computer Science  
It is used as one of the major knowledge representation mechanism for semantic web. Introducing the ontology knowledge provides more relevant search results for the users information need.  ...  The combination of Fuzzy and Ontology based information retrieval provides better results as they mainly deal with the semantics and the uncertainty of information.  ...  Keyword Optimization Techniques for Information Retrieval The present Information Retrieval (IR) method provide a secure path for the user to state the information requires on the basis of keywords but  ... 
doi:10.1016/j.procs.2015.04.075 fatcat:lapkeusytzfirharigor2ntnca

Design of University Library and Information Management System Based on Big Data Fusion

Jia Zhang, Yansong Wang
2018 MATEC Web of Conferences  
The feature quantity of semantic concept set of library information is extracted, and the classification storage and information retrieval of library information is carried out by fuzzy clustering method  ...  The adaptive training method is used for feature fusion, and big data fusion of library and information is realized in high dimensional feature space.  ...  In reference [6] , a method for optimizing the retrieval of university library and information is proposed based on the fusion clustering of relevance semantics, and the distributed structure model of  ... 
doi:10.1051/matecconf/201823201010 fatcat:nquus6upcfcrthu6xcuq3sxm5u

Active Concept Learning in Image Databases

A. Dong, B. Bhanu
2005 IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics)  
Experimental results on Corel database show the efficacy of our active concept learning approach and the improvement in retrieval performance by concept transduction.  ...  Concept learning in content-based image retrieval systems is a challenging task.  ...  For a clustering task with regard to a mixture model, if different sets of feature data belonging to different clusters (concepts) are well separated, it is very likely that some clustering algorithm merely  ... 
doi:10.1109/tsmcb.2005.846653 pmid:15971914 fatcat:prrpcpeqh5gbtfqpeecrsyjyti

Contribution-based clustering algorithm for content-based image retrieval

Harikrishna Narasimhan, Purushothaman Ramraj
2010 2010 5th International Conference on Industrial and Information Systems  
We apply the algorithm to content-based image retrieval and compare its performance with that of the k-means clustering algorithm.  ...  Unlike the k-means algorithm, our algorithm optimizes on both intra-cluster and inter-cluster similarity measures.  ...  Sridhar for a valuable discussion they had with him on data clustering.  ... 
doi:10.1109/iciinfs.2010.5578664 fatcat:eb2izl5kqzel5bsigxw6kqqwrq

Application of Convolution Neural Networks in Web Search Log Mining for Effective Web Document Clustering

Suruchi Chawla
2022 International Journal of Information Retrieval Research  
The web search log has been the source of data for mining based on web document clustering techniques to improve the efficiency and effectiveness of information retrieval.  ...  confirm the effectiveness of CNN in web search log mining for effective web document clustering.  ...  These document concept vectors are clustered to improve the quality of clustering for effective information retrieval.  ... 
doi:10.4018/ijirr.300367 fatcat:p37htwoyovcmvnsjb4bhnuhsge

Concepts Learning with Fuzzy Clustering and Relevance Feedback [chapter]

Bir Bhanu, Anlei Dong
2001 Lecture Notes in Computer Science  
We propose a semi-supervised fuzzy clustering method to learn class distribution (meta knowledge) in the sense of high-level concepts from retrieval experience.  ...  In this paper, we address the problem of incorporating prior experience of the retrieval system to improve the performance on future queries.  ...  The contents of the information do not necessarily reflect the position or the policy of the US Government.  ... 
doi:10.1007/3-540-44596-x_9 fatcat:kil7dfpftnf6zhxxxjsbetbsrm

Concepts learning with fuzzy clustering and relevance feedback

Bir Bhanu, Anlei Dong
2002 Engineering applications of artificial intelligence  
We propose a semi-supervised fuzzy clustering method to learn class distribution (meta knowledge) in the sense of high-level concepts from retrieval experience.  ...  In this paper, we address the problem of incorporating prior experience of the retrieval system to improve the performance on future queries.  ...  The contents of the information do not necessarily reflect the position or the policy of the US Government.  ... 
doi:10.1016/s0952-1976(02)00026-x fatcat:woxxazll2bbcfoy35dnouxvawu

An Integrated Harmony Search Method for Text Clustering using a Constraint based Approach

S. Siamala Devi, A. Shanmugam
2015 Indian Journal of Science and Technology  
Method: Grouping of data makes information retrieval easier. Clustering is one of the most important data mining techniques for grouping the data.  ...  Such types of applications are found existing in large. Storing and retrieval of information is always challenging task.  ...  Document clustering has been investigated for use in a number of different areas of text mining and information retrieval.  ... 
doi:10.17485/ijst/2015/v8i29/73986 fatcat:gn4emh7whrfgffcriaytilxwti

Taxonomical Associative Memory

Diogo Rendeiro, João Sacramento, Andreas Wichert
2012 Cognitive Computation  
Memory traces are stored in an uncompressed network, and each additional network codes for a taxonomical rank. Retrieval is progressive, presenting increasingly specific superordinate concepts.  ...  In a recent work, Sacramento and Wichert (in Neural Netw 24(2):143-147, 2011) proposed a hierarchical arrangement of compressed associative networks, improving retrieval time by allowing irrelevant neurons  ...  The output of concept feature-sets for the cluster at every level is detailed in Table 4 , along with the elements of said cluster (for reference).  ... 
doi:10.1007/s12559-012-9198-4 fatcat:s4vwmbmlirgtjjkibunl5k4ilu

Towards an AEC-AI Industry Optimization Algorithmic Knowledge Mapping An Adaptive Methodology for Macroscopic Conceptual Analysis

Carlos Maureira, Hernan Pinto, Victor Yepes, Jose Garcia
2021 IEEE Access  
the full-text sample retrieved for "AEC-AI Industry" and Optimization for the general query .  ...  Therefore, a complex mapping is expected around the concept of Optimization.  ... 
doi:10.1109/access.2021.3102215 fatcat:kjkbddvbcrgp3k7api3j6pkgse

Automatic Selection of Noun Phrases as Document Descriptors in an FCA-Based Information Retrieval System [chapter]

Juan M. Cigarrán, Anselmo Peñas, Julio Gonzalo, Felisa Verdejo
2005 Lecture Notes in Computer Science  
Optimal attributes as document descriptors should produce smaller, clearer and more browsable concept lattices with better clustering features.  ...  Automatic attribute selection is a critical step when using Formal Concept Analysis (FCA) in a free text document retrieval framework.  ...  Results of this phase are critical to a) reach a reasonable cardinality for the concept set; and b) reach an optimal distribution of the documents in the lattice.  ... 
doi:10.1007/978-3-540-32262-7_4 fatcat:trga3ztrorfxdoqlm3bpz47tmq

Efficient Modeling of Visual Art Color Image Clustering

Y. Poornima, P. S. Hiremath
2014 International Journal of Computer Applications  
Although there has been massive research work being conducted in the area of content-based image retrieval (CBIR) system using various sophisticated techniques, very little work has been witnessed for  ...  Keywords Content based image retrieval system, visual art image, K-Means algorithm, Clustering Techniques, Block Truncation Coding.  ...  K-means is a clustering method based on the optimization of an overall measure of clustering quality is known for its efficiency in producing accurate results in image retrieval.  ... 
doi:10.5120/15926-5192 fatcat:xvujofrrkrca5hlnkff3wdlbhu
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