3 edition of A study of the application of post-retrieval clustering in bibliographic databases found in the catalog.
A study of the application of post-retrieval clustering in bibliographic databases
Carolyn Susan Schwartz
|Statement||by Carolyn Susan (Candy) Schwartz.|
|The Physical Object|
|Pagination||1 microfilm reel|
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The Study of the Application of Post-Retrieval Clustering in Bibliographic Databases. Professor Michael McGill, Advisor. Padmini Das-Gupta, Ph.D. An Investigation into the Two Poisson Model of Automatic Indexing.
Professor Jeffrey Katzer, Advisor. Michael Eisenberg, Ph.D. Magnitude Estimation and the Measurement of Relevance. "A Study of the Application of Post-Retrieval Clustering in Bibliographic Databases." Ph.D. dissertation, Syracuse University, A study of the application of post-retrieval clustering in bibliographic databases book and Information Science Research, v.
11 (1), January-MarchAl-Dosary, Fahad Misfer. "Characteristics of Research Literature used by Political Scientists: A Study of the Influence of.
In the photo retrieval task of ImageCLEFwe examined the influence of image representations, clustering methods, and query types in enhancing result diversity. Two types of visual concept vectors and hierarchical and partitioning clustering as post-retrieval clustering methods were by: 2.
papers from information processing & management, and information storage and retrieval, Post-retrieval clustering is the task of clustering Web search results.
Within this context, we propose a new methodology that adapts the classical. Grouper is, to our knowledge, the first implementation of a post-retrieval document-clustering interface to a Web search ed by STC's success, we studied the use of phrases for.
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. • I. Varlamis and G.
Tsatsaronis, "Visualizing Bibliographic Databases as Graphs and Mining Potential Research Synergies", International Conference on Social Networks Analysis and Mining (ASONAM ), JulyTaiwan. Vol is The extraction of community structures from publication networks to support ethnographic observations of field differences in scientific communication pp.
Theresa Velden and Carl Lagoze Characteristics of retracted open access biomedical literature: A bibliographic analysis pp. Gabriel M. Peterson. Full text of "Information Retrieval: A survey" See other formats. Biography. Hsinchun Chen is University of Arizona Regents’ Professor and Thomas R.
Brown Chair in Management and Technology in the Management Information Systems (MIS) Department and Professor of Entrepreneurship & Innovation in the McGuire Center for Entrepreneurship at the College of Management of the University of Arizona.
He received the B.S. degree from the. Interactive search result clustering: a study of user behavior and retrieval effectiveness (XG, WK, YZ, RB), pp. – JCDLPuginZ #music Instrument distribution and music notation search for enhancing bibliographic music score retrieval (LP, RZ), pp. – Full text of "Ranganathan’s Philosophy - Assessment, Impact And Relevance" See other formats.
NHS CFHEP Extension: Final report The Impact of eHealth on the Quality and Safety of Healthcare An updated systematic overview & synthesis of the literature Final report for the NHS Connecting for Health Evaluation Programme (NHS CFHEP ) Aziz Sheikh, Susannah McLean, Kathrin Cresswell, Claudia Pagliari, Yannis Pappas, Josip Car, Ashly Black, Akiko.
The impact of a formal framework for temporal granularities has been deeply investigated for a number of application areas among which logical design of temporal databases, querying databases in terms of arbitrary granularities, data mining. Multilingual Information Retrieval (MLIR) refers to the ability to process a query for information in any language, search a collection of objects, including text, images, sound files, etc., and return the most relevant objects, translated if necessary into the user's language.
The explosion in recent years of freely-distributed unstructured. The query-performance prediction task is estimating the effectiveness of a search performed in response to a query when no relevance judgments are available. Although there existCited by: Raymond E. Mineck, Study of Potential Aerodynamic Benefits From Spanwise Blowing at Wingtip, NASA TP, Junepp.
This report is an expanded version of a thesis submitted in partial fulfillment of the requirements for the Degree of Doctor of Science, George Washington University, Washington, D.C., May It is time-aware and rewards posts that are published in or near a burst of posts that are ranked highly in many of the lists being aggregated.
Our experimental results show that it significantly outperforms state-of-the-art rank aggregation and time-sensitive microblog search by: Mining Social Media: Tracking Content and Predicting Behavior ACADEMISCH PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magniﬁcus D.C.
van den Boom ten overstaan van een door het college voor promoties ingestelde commissie, in het openbaar te verdedigen in de. Document clustering is an important tool for text analysis and is used in many different applications.
We propose to incorporate prior knowledge of cluster membership for document cluster analysis and develop a novel semi-supervised document clustering.
• references not having an a priori IT focus or objective but that reported on IT post retrieval of references25;26 We subsequently found that many studies employed systematic review methodology to simply describe the past and or current state of the literature for medical or health informatics in general,27 or in particular geographical.
Silva, ; Milidiu, R.L. – Belief function model for information retrieval (Lang.: eng). - In: Proposal to use the Belief Function Model for automatic indexing and ranking with respect to a given user model is based on a controlled vocabulary and on term frequencies in each is wider in scope than the.
1 1. 1 2. 1 3. 1 4. 1 92 5. The faceted databases are completely different and actually use a completely different meaning for 'faceted' - it is not the extraction of terms from documents as the analysis engines do.
The faceted databases (as Josh Ferraro described) aggregate values from fields of their records, and then display them to the users. Visual monitoring of autonomous life sciences experimentation.
NASA Technical Reports Server (NTRS) Blank, G. E.; Martin, W. The design and implementation of a comp. The Bibliographic Retrieval System (BARS) is a data base management system specially designed to retrieve bibliographic references. Two databases are available, (i) the Sandia Shock Compression (SSC) database which contains over references to the literature related to stress waves in solids and their applications, and (ii) the Shock.
Cataloging-in-Publication Data applied for A catalog record for this book is available from the Library of Congress Bibliographic information published by Die Deutsche Bibliothek Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliographie; detailed bibliographic data is available in the Internet at.
- A novel approach for estimating the omitted-citation rate of bibliometric databases with an application to the field of bibliomentrics (Lang.: eng). - In: Journal of the American Society for Information Science & Technology, 64()10, pp.
Clustering and Rules-based Approach This method [Chen and Zhang, ] uses clustering to perform seg-mentation of the query and then chooses the sub-query from among those clusters.
The detailed method is as follows. Retrieve several short queries P related to a long query Q from the users query history. The topics include: experimental study on the transverse stiffness of WJ-8 rail fastening; research on modeling and characteristics of two-stage pressure hydro-pneumatic spring; study on torsion-eliminating performance of laterally interconnected air suspension; simulation on kinetic characteristics of moving mooring marine current turbine.
In order to study this problem, this paper presents a new algorithm, called ICS, which aims to discover natural network communities by inferring from the local information of nodes inherently hidden in networks based on a new centrality, that is, clustering centrality, which is a generalization of eigenvector centrality.
Our future work includes: study on problem space, improvement of performance, discovery of h-DESAR on data streams, and application of web mining or firewall log mining. References  Agrawal R, Imiclinski T, Swami A. Database mining: A performance perspective [J].