An Inductive Search System: Theory, Design, and Implementation

Maron, M. E.; Curry, Sean; Thompson, Paul

doi:10.1109/tsmc.1986.289278

Cited by 26 publications

(14 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Numerous attempts have been made by researchers in both academia and industry to semi-automate/ automate the process of finding the right expert. These include: HelpNet (Maron, 1986), Expert/ Expert-locator (Streeter & Lochbaum, 1988) , ContactFinder (Krulwich and Burkey, 1996), Agent Amplified Communication (Kautz et al, 1996), Yenta (Foner, 1997), Phoaks (Terveen, 1997), Expertise Browser (Cohen et al, 1998), MEMOIR (Pikrakis et al, 1998), Expertise Recommender (McDonald andAckerman, 1998), MIT's Expert Finder (Mattox et al, 1999), InfoScout (Prasad and Nagendra, 1999), SAGE (Becerra-Fernandez, 1999) and the KCSR Expert Finder (Crowder, 2002) (Recommind, Inc. , 2011), and many others.…”

Section: Expertise Locator Approachesmentioning

confidence: 99%

The design and evaluation of EKE, a semi-automated email knowledge extraction tool

Tedmori

Jackson

2012

Knowledge Management Research & Practice

View full text Add to dashboard Cite

Section: Expertise Locator Approachesmentioning

confidence: 99%

The design and evaluation of EKE, a semi-automated email knowledge extraction tool

Tedmori

Jackson

2012

Knowledge Management Research & Practice

View full text Add to dashboard Cite

Section: Related Workmentioning

confidence: 99%

“…For example in automatic expert finding system, HelpNet [5] and Expert/Expert-Locator (EEL) [6] [7]. [5] allow user filled information to provide the expertise profile and [6][7] use a representative collection of user's technical document to build the expertise index. There are a lot of previous system that use textual analysis as the basis for expert finding but [9] uses graph analysis to find interlinked cliques for interest group and [10] that uses users' visit path record of experts.…”

Section: Related Workmentioning

confidence: 99%

Community Search: A Collaborative Searching Web Application with a User Ranking System

Yongpisanpop

Ohira

Matsumoto

2011

Online Communities and Social Computing

View full text Add to dashboard Cite

Abstract. People are using search engine in daily life. But most of the tools that we have today treat information-seeking tasks as a transient activity. In this research paper we introduce a web application system that provides collaborative function and experts finding system. We develop a system that will help user to organize search result and to do the collaboration with others. With the new iterative algorithm, users will also gain more percentage of needed result and the system will be able to suggest the experts related to the search keyword.

show abstract

“…Attempts to develop systems that exploit implicit evidence of expertise to augment the process of finding the right expert dates back at least to the visionary work of Maron and his colleagues [17]. Their experimental system, called HelpNet, accepts requests for information and responds with names of people ranked by the probability that the individual will provide a satisfactory answer.…”

Section: Automatic Expert Findersmentioning

confidence: 99%

Expert-Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach

Yimam-Seid¹,

Kobsa

2003

Journal of Organizational Computing and Electronic Commerce

153

View full text Add to dashboard Cite

Computer systems that augment the process of finding the right expert for a given problem in an organization or world-wide are becoming feasible more than ever before, thanks to the prevalence of corporate Intranets and the Internet. This paper investigates such systems in two parts. We first explore the expert finding problem in depth, review and analyze existing systems in this domain, and suggest a domain model that can serve as a framework for design and development decisions. Based on our analyses of the problem and solution spaces, we then bring to light the gaps that remain to be addressed. Finally, we present our approach called DEMOIR, which is a modular architecture for expert finding systems that is based on a centralized expertise modeling server while also incorporating decentralized components for expertise information gathering and exploitation.

show abstract

An Inductive Search System: Theory, Design, and Implementation

Cited by 26 publications

References 17 publications

The design and evaluation of EKE, a semi-automated email knowledge extraction tool

The design and evaluation of EKE, a semi-automated email knowledge extraction tool

Community Search: A Collaborative Searching Web Application with a User Ranking System

Expert-Finding Systems for Organizations: Problem and Domain Analysis and the DEMOIR Approach

Contact Info

Product

Resources

About