Collaborative information retrieval environment: integration of information retrieval with group support systems

Romano, Nicholas C.; Nunamaker, Jay F.; Roussinov, Dmitri; Chen, Hsinshun

doi:10.1109/hicss.1999.772729

Cited by 41 publications

(38 citation statements)

References 72 publications

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“…Bu yıldan sonra ortak bilgi davranışını destekleyecek bir dizi çalışma birbirini takip etmiştir. Twidale ve Nichols (1998), ortak bilgi aramayı destekleyecek bir arayüz (ARIADNE) geliştirmiş, McDonald ve Ackerman (1998), Koschmann ve Stahl (1998), Cohen, Maglio, ve Barret (1998) ve Romano, Roussinov, Nunamaker ve Chen (1999), ortak bilgi davranışını destekleyecek deneysel teknolojik çözümler üzerindeki ilk çalışmaları başlatmışlardır. Ayrıca Reddy, Jansen ve Spence (2010) tarafından yapılan araştırma ile üretilen MUSE adlı prototip ile, iki kullanıcının arama sonuçlarını birbirleriyle paylaşabildikleri ve aynı anda görüşebildikleri (chat) bir çoklu kullanıcılı arama motoru geliştirilmiştir.…”

Section: Ortak Bilgi Davranışı (Obd)unclassified

Bireyselden Ortak Bilgi Davranışına

Yıldız

Uçak

2014

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Section: Ortak Bilgi Davranışı (Obd)unclassified

Bireyselden Ortak Bilgi Davranışına

Yıldız

Uçak

2014

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“…Orlikowski (1992) observed that Lotus Notes was not well utilized because workers had little or no incentive to share information. The situation, however, becomes less problematic for Web search, which consists mostly of voluntary contributions (Romano et al, 1999). Users are more willing to contribute in exchange of pride and popularity.…”

Section: Collaborative Information Retrieval and Collaborative Filteringmentioning

confidence: 99%

“…Annotations in free-text or predefined formats are also incorporated in systems such as AntWorld (Kantor et al, 2000), Annotate! (Ginsburg, 1998), and CIRE (Romano et al, 1999) to facilitate collaboration retrieval among users.…”

Section: Collaborative Information Retrieval and Collaborative Filteringmentioning

confidence: 99%

Searching and mining the web for personalized and specialized information

Chau

2005

SIGIR Forum

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With the rapid growth of the Web, users are often faced with the problem of information overload and find it difficult to search for relevant and useful information on the Web. Besides general-purpose search engines, there exist some alternative approaches that can help users perform searches on the Web more effectively and efficiently. Personalized search agents and specialized search engines are two such approaches. The goal of this research is to investigate how machine learning and artificial intelligence techniques can be used to improve these approaches.

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“…Annotations in free text or predefined formats are also incorporated in systems such as AntWorld [21], Annotate! [16], and CIRE [35] to facilitate collaborative retrieval among users.…”

Section: Collaborative Information Retrieval and Collaborative Filteringmentioning

confidence: 99%

Design and evaluation of a multi-agent collaborative Web mining system

Chau

Zeng

Chen

et al. 2003

Decision Support Systems

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Most existing Web search tools work only with individual users and do not help a user benefit from previous search experiences of others. In this paper, we present the Collaborative Spider, a multi-agent system designed to provide post-retrieval analysis and enable across-user collaboration in Web search and mining. This system allows the user to annotate search sessions and share them with other users. We also report a user study designed to evaluate the effectiveness of this system. Our experimental findings show that subjects' search performance was degraded, compared to individual search scenarios in which users had no access to previous searches, when they had access to a limited number (e.g., 1 or 2) of earlier search sessions done by other users. However, search performance improved significantly when subjects had access to more search sessions. This indicates that gain from collaboration through collaborative Web searching and analysis does not outweigh the overhead of browsing and comprehending other users' past searches until a certain number of shared sessions have been reached. In this paper, we also catalog and analyze several different types of user collaboration behavior observed in the context of Web mining. D

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Collaborative information retrieval environment: integration of information retrieval with group support systems

Abstract: Observations of Information Retrieval (IR)

Cited by 41 publications

References 72 publications

Bireyselden Ortak Bilgi Davranışına

Bireyselden Ortak Bilgi Davranışına

Searching and mining the web for personalized and specialized information

Design and evaluation of a multi-agent collaborative Web mining system

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