Publication statistics

Pub. period:1987-2007
Pub. count:26
Number of co-authors:38



Co-authors

Number of publications with 3 favourite co-authors:

Zonghuan Wu:7
Jitender S. Deogun:4
Venkat N. Gudivada:3

 

 

Productive colleagues

Vijay V. Raghavan's 3 most productive colleagues in number of publications:

Clement T. Yu:22
Weiyi Meng:22
Jitender S. Deogun:13
 
 
 

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Vijay V. Raghavan

Has also published under the name of:
"Vijay Raghavan"

Personal Homepage:
http://www.nku.edu/~raghavan/

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Publications by Vijay V. Raghavan (bibliography)

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2007
 
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Xie, Ying and Raghavan, Vijay V. (2007): Language-modeling kernel based approach for information retrieval. In JASIST - Journal of the American Society for Information Science and Technology, 58 (14) pp. 2353-2365.

 
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Chu, Shixian, Chen, Jinfeng, Wu, Zonghuan, Chu, Chee-Hung Henry and Raghavan, Vijay V. (2007): A Treemap-Based Result Interface for Search Engine Users. In: Smith, Michael J. and Salvendy, Gavriel (eds.) Symposium on Human Interface 2007 - Part I July 22-27, 2007, Beijing, China. pp. 401-410.

2006
 
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Shah, Biren, Raghavan, Vijay V., Dhatric, Praveen and Zhao, Xiaoquan (2006): A cluster-based approach for efficient content-based image retrieval using a similarity-preserving space transformation method. In JASIST - Journal of the American Society for Information Science and Technology, 57 (12) pp. 1694-1707.

2005
 
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Zhao, Hongkun, Meng, Weiyi, Wu, Zonghuan, Raghavan, Vijay V. and Yu, Clement (2005): Fully automatic wrapper generation for search engines. In: Proceedings of the 2005 International Conference on the World Wide Web 2005. pp. 66-75.

When a query is submitted to a search engine, the search engine returns a dynamically generated result page containing the result records, each of which usually consists of a link to and/or snippet of a retrieved Web page. In addition, such a result page often also contains information irrelevant to the query, such as information related to the hosting site of the search engine and advertisements. In this paper, we present a technique for automatically producing wrappers that can be used to extract search result records from dynamically generated result pages returned by search engines. Automatic search result record extraction is very important for many applications that need to interact with search engines such as automatic construction and maintenance of metasearch engines and deep Web crawling. The novel aspect of the proposed technique is that it utilizes both the visual content features on the result page as displayed on a browser and the HTML tag structures of the HTML source file of the result page. Experimental results indicate that this technique can achieve very high extraction accuracy.

© All rights reserved Zhao et al. and/or ACM Press

 
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Ramachandran, Karthik, Shah, Biren and Raghavan, Vijay V. (2005): Dynamic Pre-fetching of Views Based on User-Access Patterns in an OLAP System. In: Chen, Chin-Sheng, Filipe, Joaquim, Seruca, Isabel and Cordeiro, Jos (eds.) ICEIS 2005 - Proceedings of the Seventh International Conference on Enterprise Information Systems May 25-28, 2005, Miami, USA. pp. 60-67.

2004
 
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Yao, Jingtao, Raghavan, Vijay V. and Wang, G. Y. (eds.) Proceedings of the 2nd International Workshop on Web-based Support Systems September 20, 2004, Beijing, China.

 
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Diaz, Elizabeth D., De, Arijit and Raghavan, Vijay V. (2004): On Selective Result Merging in a Metasearch Enviroment. In: Yao, Jingtao, Raghavan, Vijay V. and Wang, G. Y. (eds.) Proceedings of the 2nd International Workshop on Web-based Support Systems September 20, 2004, Beijing, China. pp. 52-59.

 
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Karnatapu, Surendra, Ramachandran, Karthik, Wu, Zonghuan, Shah, Biren, Raghavan, Vijay V. and Benton, Ryan (2004): Estimating Size of Search Engines in an Uncooperative Environment. In: Yao, Jingtao, Raghavan, Vijay V. and Wang, G. Y. (eds.) Proceedings of the 2nd International Workshop on Web-based Support Systems September 20, 2004, Beijing, China. pp. 81-87.

 
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Mehra, Ritesh, Gandham, Satya K., Wu, Zonghuan and Raghavan, Vijay V. (2004): Configuring Java-Based Web Application Development Environment for an Academic Setting. In: Yao, Jingtao, Raghavan, Vijay V. and Wang, G. Y. (eds.) Proceedings of the 2nd International Workshop on Web-based Support Systems September 20, 2004, Beijing, China. pp. 111-118.

 
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Wu, Zonghuan, Mundluru, Dheerendranath and Raghavan, Vijay V. (2004): Automatically Detecting Boolean Operations Supported by Search Engines, Towards Search Engine Query Language Discovery. In: Yao, Jingtao, Raghavan, Vijay V. and Wang, G. Y. (eds.) Proceedings of the 2nd International Workshop on Web-based Support Systems September 20, 2004, Beijing, China. pp. 171-178.

2003
 
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Wu, Zonghuan, Raghavan, Vijay V., Du, Chun, C, Komanduru Sai, Meng, Weiyi, He, Hai and Yu, Clement (2003): SE-LEGO: creating metasearch engines on demand. In: Proceedings of the 26th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 2003. p. 464.

 
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Wu, Zonghuan, Raghavan, Vijay V., Qian, Hua, Rama, Vuyyuru, Meng, Weiyi, He, Hai and Yu, Clement T. (2003): Towards Automatic Incorporation of Search Engines into a Large-Scale Metasearch Engine. In: 2003 IEEE / WIC International Conference on Web Intelligence - WI 2003 13-17 October, 2003, Halifax, Canada. pp. 658-661.

2002
 
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Noel, Steven, Chu, Chee-Hung Henry and Raghavan, Vijay V. (2002): Visualization of Document Co-Citation Counts. In: IV 2002 2002. pp. 691-696.

1998
 
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Bollmann-Sdorra, Peter and Raghavan, Vijay V. (1998): On the Necessity of Term Dependence in a Query Space for Weighted Retrieval. In JASIST - Journal of the American Society for Information Science and Technology, 49 (13) pp. 1161-1168.

 
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Deogun, Jitender S., Choubey, Suresh K., Raghavan, Vijay V. and Sever, Hayri (1998): Feature Selection and Effective Classifiers. In JASIST - Journal of the American Society for Information Science and Technology, 49 (5) pp. 423-434.

 
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Raghavan, Vijay V., Deogun, Jitender S. and Sever, Hayri (1998): Introduction (Special Topic Issue: Knowledge Discovery and Data Mining). In JASIST - Journal of the American Society for Information Science and Technology, 49 (5) pp. 397-402.

1997
 
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Gudivada, Venkat N., Raghavan, Vijay V., Grosky, William I. and Kasanagottu, Rajesh (1997): Information Retrieval on the World Wide Web. In IEEE Internet Computing, 1 (5) pp. 58-68.

1996
 
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Raghavan, Vijay V. (1996): Measurement in Information Science, by Bert R. Boyce, Charles T. Meadow, and Donald H. Kraft. In JASIST - Journal of the American Society for Information Science and Technology, 47 (3) pp. 257-258.

1995
 
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Gudivada, Venkat N. and Raghavan, Vijay V. (1995): Design and Evaluation of Algorithms for Image Retrieval by Spatial Similarity. In ACM Transactions on Information Systems, 13 (2) pp. 115-144.

Similarity-based retrieval of images is an important task in many image database applications. A major class of users' requests requires retrieving those images in the database that are spatially similar to the query image. We propose an algorithm for computing the spatial similarity between two symbolic images. A symbolic image is a logical representation of the original image where the image objects are uniquely labeled with symbolic names. Spatial relationships in a symbolic image are represented as edges in a weighted graph referred to as spatial-orientation graph. Spatial similarity is then quantified in terms of the number of, as well as the extent to which, the edges of the spatial-orientation graph of the database image conform to the corresponding edges of the spatial-orientation graph of the query image. The proposed algorithm is robust in the sense that it can deal with translation, scale, and rotational variances in images. The algorithm has quadratic time complexity in terms of the total number of objects in both the database and query images. We also introduce the idea of quantifying a system's retrieval quality by having an expert specify the expected rank ordering with respect to each query for a set of test queries. This enables us to assess the quality of algorithms comprehensively for retrieval in image databases. The characteristics of the proposed algorithm are compared with those of the previously available algorithms using a testbed of images. The comparison demonstrated that our algorithm is not only more efficient but also provides a rank ordering of images that consistently matches with the expert's expected rank ordering.

© All rights reserved Gudivada and Raghavan and/or ACM Press

 
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Raghavan, Vijay V. and Sever, Hayri (1995): On the Reuse of Past Optimal Queries. In: Proceedings of the Eighteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1995. pp. 344-350.

Information Retrieval (IR) systems exploit user feedback by generating an optimal query with respect to a particular information need. Since obtaining an optimal query is an expensive process, the need for mechanisms to save and reuse past optimal queries for future queries is obvious. In this article, we propose the use of a query base, a set of persistent past optimal queries, and investigate similarity measures between queries. The query base can be used either to answer user queries or to formulate optimal queries. We justify the former case analytically and the latter case by experiment.

© All rights reserved Raghavan and Sever and/or ACM Press

 
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Gudivada, Venkat N. and Raghavan, Vijay V. (1995): Content-Based Image Retrieval Systems - Guest Editors' Introduction. In IEEE Computer, 28 (9) pp. 18-22.

1993
 
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Bollmann-Sdorra, Peter and Raghavan, Vijay V. (1993): On the Delusiveness of Adopting a Common Space for Modeling IR Objects: Are Queries Documents. In JASIST - Journal of the American Society for Information Science and Technology, 44 (10) pp. 579-587.

1991
 
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Zhang, Yong, Raghavan, Vijay V. and Deogun, Jitender S. (1991): An Object-Oriented Modeling of the History of Optimal Retrievals. In: Proceedings of the Fourteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1991. pp. 241-250.

Learning techniques are used in IR to exploit user feedback in order that the system can improve its performance with respect to particular queries. This process involves the construction of an optimal query that best separates the documents known to be relevant from those that are not. Since obtaining relevance judgments and constructing an optimal query involve a great deal of effort, in this paper, we develop a framework for organizing the history of optimal retrievals. The framework involves the identification 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. The ways in which such a hierarchy may be used to retrieve answers to new queries are outlined. This approach has the advantage that the query specification is concept-based, where as the retrieval mechanism is numerically-oriented involving optimal query vectors. It is shown that the construction of a hierarchy of optimal queries can correspond to an object-oriented modeling of IR objects. Furthermore, the resulting model can be easily implemented using a relational DBMS.

© All rights reserved Zhang et al. and/or ACM Press

1989
 
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Raghavan, Vijay V., Jung, Gwang S. and Bollmann, Peter (1989): A Critical Investigation of Recall and Precision as Measures of Retrieval System Performance. In ACM Transactions on Information Systems, 7 (3) pp. 205-229.

Recall and precision are often used to evaluate the effectiveness of information retrieval systems. They are easy to define if there is a single query and if the retrieval result generated for the query is a linear ordering. However, when the retrieval results are weakly ordered, in the sense that several documents have an identical retrieval status value with respect to a query, some probabilistic notion of precision has to be introduced. Relevance probability, expected precision, and so forth, are some alternatives mentioned in the literature for this purpose. Furthermore, when many queries are to be evaluated and the retrieval results averaged over these queries, some method of interpolation of precision values at certain preselected recall levels is needed. The currently popular approaches for handling both a weak ordering and interpolation are found to be inconsistent, and the results obtained are not easy to interpret. Moreover, in cases where some alternatives are available, no comparative analysis that would facilitate the selection of a particular strategy has been provided. In this paper, we systematically investigate the various problems and issues associated with the use of recall and precision as measures of retrieval system performance. Our motivation is to provide a comparative analysis of methods available for defining precision in a probabilistic sense and to promote a better understanding of the various issues involved in retrieval performance evaluation.

© All rights reserved Raghavan et al. and/or ACM Press

1988
 
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Bollmann, Peter and Raghavan, Vijay V. (1988): A Utility-Theoretic Analysis of Expected Search Length. In: Proceedings of the Eleventh Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1988. pp. 245-256.

In this paper the expected search length, which is a measure of retrieval system performance, is investigated from the viewpoint of axiomatic utility theory. Necessary and sufficient criteria for the expected search length to be an ordinal scale and sufficient criteria that it is a ratio scale are given.

© All rights reserved Bollmann and Raghavan and/or ACM Press

1987
 
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Raghavan, Vijay V. and Deogun, Jitender S. (1987): Optimal Determination of User-Oriented Clusters. In: Proceedings of the Tenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval 1987. pp. 140-146.

User-oriented clustering schemes enable the classification of documents based upon the user perception of the similarity between documents, rather than on some similarity function presumed by the designer to represent the user criteria. In this paper, an enhancement of such a clustering scheme is presented. This is accomplished by the formulation of the user-oriented clustering as a function-optimization problem. The problem formulated is termed the Boundary Selection Problem (BSP). Heuristic approaches to solve the BSP are proposed and a preliminary for evaluation of these approaches is provided.

© All rights reserved Raghavan and Deogun and/or ACM Press

 
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Page Information

Page maintainer: The Editorial Team
URL: http://www.interaction-design.org/references/authors/vijay_v__raghavan.html

Publication statistics

Pub. period:1987-2007
Pub. count:26
Number of co-authors:38



Co-authors

Number of publications with 3 favourite co-authors:

Zonghuan Wu:7
Jitender S. Deogun:4
Venkat N. Gudivada:3

 

 

Productive colleagues

Vijay V. Raghavan's 3 most productive colleagues in number of publications:

Clement T. Yu:22
Weiyi Meng:22
Jitender S. Deogun:13
 
 
 

Upcoming Courses

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User Experience and Experience Design !

 
 

Our Latest Books

 
 
The Social Design of Technical Systems: Building technologies for communities. 2nd Edition
by Brian Whitworth and Adnan Ahmad
start reading
 
 
 
 
Gamification at Work: Designing Engaging Business Software
by Janaki Mythily Kumar and Mario Herger
start reading
 
 
 
 
The Social Design of Technical Systems: Building technologies for communities
by Brian Whitworth and Adnan Ahmad
start reading
 
 
 
 
The Encyclopedia of Human-Computer Interaction, 2nd Ed.
by Mads Soegaard and Rikke Friis Dam
start reading