Search (26 results, page 2 of 2)

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Abstract

Autonomy's Classification solutions remove the necessity for organizations to rely on human intervention or manual processing of information, such as manual tagging, typically required to make most other e-business applications work. Autonomy's ability to consistently and accurately classify data automatically is a unique infrastructure solution that overcomes the predicaments surrounding the exponential growth of unstructured data.

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Content

Ramana Rao (Inxight, Palo Alto, CA) 7 ± 2 Insights on achieving Effective Information Access Session One: Updates and a twelve month perspective Danny Sullivan (Search Engine Watch, US / England) Portalization and other search trends Carol Tenopir (University of Tennessee) Search realities faced by end users and professional searchers Session Two: Today's search engines and beyond Daniel Hoogterp (Retrieval Technologies, McLean, VA) Effective presentation and utilization of search techniques Rick Kenny (Fulcrum Technologies, Ontario, Canada) Beyond document clustering: The knowledge impact statement Gary Stock (Ingenius, Kalamazoo, MI) Automated change monitoring Gary Culliss (Direct Hit, Wellesley Hills, MA) User popularity ranked search engines Byron Dom (IBM, CA) Automatically finding the best pages on the World Wide Web (CLEVER) Peter Tomassi (LookSmart, San Francisco, CA) Adding human intellect to search technology Session Three: Panel discussion: Human v automated categorization and editing Ev Brenner (New York, NY)- Chairman James Callan (University of Massachusetts, MA) Marc Krellenstein (Northern Light Technology, Cambridge, MA) Dan Miller (Ask Jeeves, Berkeley, CA) Session Four: Updates and a twelve month perspective Steve Arnold (AIT, Harrods Creek, KY) Review: The leading edge in search and retrieval software Ellen Voorhees (NIST, Gaithersburg, MD) TREC update Session Five: Search engines now and beyond Intelligent Agents John Snyder (Muscat, Cambridge, England) Practical issues behind intelligent agents Text summarization Therese Firmin, (Dept of Defense, Ft George G. Meade, MD) The TIPSTER/SUMMAC evaluation of automatic text summarization systems Cross language searching Elizabeth Liddy (TextWise, Syracuse, NY) A conceptual interlingua approach to cross-language retrieval. Video search and retrieval Armon Amir (IBM, Almaden, CA) CueVideo: Modular system for automatic indexing and browsing of video/audio Speech recognition Michael Witbrock (Lycos, Waltham, MA) Retrieval of spoken documents Visualization James A. Wise (Integral Visuals, Richland, WA) Information visualization in the new millennium: Emerging science or passing fashion? Text mining David Evans (Claritech, Pittsburgh, PA) Text mining - towards decision support

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Abstract

Emerging standards in knowledge representation and organization are preparing the way for distributed vocabulary support in Internet search services. NetLab researchers are exploring several innovative solutions for searching and browsing in the subject-based Internet gateway, Electronic Engineering Library, Sweden (EELS). The implementation of the EELS service is described, specifically, the generation of the robot-gathered database 'All' engineering and the automated application of the Ei thesaurus and classification scheme. NetLab and OCLC researchers are collaborating to investigate advanced solutions to automated classification in the DESIRE II context. A plan for furthering the development of distributed vocabulary support in Internet search services is offered.

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Content

1. Increased Importance of Knowledge Organization in Internet Services - 2. Quality Subject Service and the role of classification - 3. Developing the DDC into a knowledge organization instrument for the digital library. OCLC site - 4. DESIRE's Barefoot Solutions of Automatic Classification - 5. Advanced Classification Solutions in DESIRE and CORC - 6. Future directions of research and development - 7. General references

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Abstract

In this document we describe the final release of the toolset for entity and semantic associations, integrating two versions (language dependent and language independent) of Unsupervised Document Similarity implemented by MU (using gensim tool) and Citation Indexing, Resolution and Matching (UJF/CMD). We give a brief description of tools, the rationale behind decisions made, and provide elementary evaluation. Tools are integrated in the main project result, EuDML website, and they deliver the needed functionality for exploratory searching and browsing the collected documents. EuDML users and content providers thus benefit from millions of algorithmically generated similarity and citation links, developed using state of the art machine learning and matching methods.

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Abstract

Das VZG-Projekt Colibri/DDC beschäftigt sich seit 2003 mit automatischen Verfahren zur Dewey-Dezimalklassifikation (Dewey Decimal Classification, kurz DDC). Ziel des Projektes ist eine einheitliche DDC-Erschließung von bibliografischen Titeldatensätzen und eine Unterstützung der DDC-Expert(inn)en und DDC-Laien, z. B. bei der Analyse und Synthese von DDC-Notationen und deren Qualitätskontrolle und der DDC-basierten Suche. Der vorliegende Bericht konzentriert sich auf die erste größere automatische DDC-Klassifizierung und erste automatische und intellektuelle Bewertung mit der Klassifizierungskomponente vc_dcl1. Grundlage hierfür waren die von der Deutschen Nationabibliothek (DNB) im November 2007 zur Verfügung gestellten 25.653 Titeldatensätze (12 Wochen-/Monatslieferungen) der Deutschen Nationalbibliografie der Reihen A, B und H. Nach Erläuterung der automatischen DDC-Klassifizierung und automatischen Bewertung in Kapitel 2 wird in Kapitel 3 auf den DNB-Bericht "Colibri_Auswertung_DDC_Endbericht_Sommer_2008" eingegangen. Es werden Sachverhalte geklärt und Fragen gestellt, deren Antworten die Weichen für den Verlauf der weiteren Klassifizierungstests stellen werden. Über das Kapitel 3 hinaus führende weitergehende Betrachtungen und Gedanken zur Fortführung der automatischen DDC-Klassifizierung werden in Kapitel 4 angestellt. Der Bericht dient dem vertieften Verständnis für die automatischen Verfahren.