A PDD-Based Searching Approach for Expert Finding in Intranet Information Management

Fu, Yupeng; Xiang, Rongjing; Zhang, Min; Liu, Yiqun; Ma, Shaoping

doi:10.1007/11880592_4

Cited by 9 publications

(16 citation statements)

References 2 publications

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“…Since the last decade, researchers have examined the search for experts from various research perspectives such as expert search system (Hawking 2004;Fu et al 2006;Balog and de Rijke 2007;Chen et al 2007;Haruechaiyasak 2009;Karimzadehgan, White and Richardson 2009;Tu et al2010), construction of expert profiles (Whittaker et al 1997;Ackerman and Halverson 1998;Crasswell et al 2001;Krulwich and Burkey 1995;Mockus and Herbsleb 2002;Yiman-Seid and Kobsa 2003;Trajkova and Gauch 2004;Liu et al 2005;Fu et al 2006;Yang et al 2008 ;Serdyukov 2009;Reichling and Wulf 2009;Stankovic et al 2010), identification of expert (Hinds 1999;McDonald 2001;Pipek et al 2003;) and ontology. This literature review has critically evaluated expert tracking system, expert profile and ontology on expert.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Previous researchers have examined the profile of experts from various angles such as research in the construction of expert profiles (Whittaker et al 1997;Ackerman and Halverson 1998;Crasswell et al 2001;Mockus and Herbsleb 2002;Yimam-Seid et al 2003;Trajkova dan Gauch 2004;Liu et al 2005;Fu et al 2006;Serdyukov 2009;and Reichling and Wulf 2009) and the identification of expert and use of research information (Wu et al 2010;Latif et al 2010). Expert search approach begins with the search by using profile information to obtain results matching the experts (Crasswell et al 2001;Liu et al 2005).…”

Section: Expert Tracking Systemmentioning

confidence: 99%

“…Fu et al (2006) have designed the description document model known as 'Person Description Document' for a more effective search for experts. Information such as the features and context of the relevant experts are extracted to build an expert profile known as self description documents for experts.…”

Section: Journal Of Organizational Knowledge Managementmentioning

confidence: 99%

“…In addition, documents containing information of different experts that are found in different formats such as in HTML, PDF and WORD, complicate the extraction process and the consolidation of useful information. Fu et al (2006) found two major problems encountered in searching experts in the organizations. First, the information on experts are distributed across organizations from different sources and in different formats.…”

Section: Journal Of Organizational Knowledge Managementmentioning

confidence: 99%

“…Second, most of the information on experts is not fully documented and only part of the document contains information on the experts involved. To overcome these problems, Fu et al (2006) used Person Description Document (PDD) to compile expert information to a central unit that can be used to profile experts. The advantage of using the self description document is to enable the extraction of expert information to be more flexible and easier to read.…”

Section: Journal Of Organizational Knowledge Managementmentioning

confidence: 99%

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A Framework for the Construction of Ontology for ICT Experts

Aris¹,

Salim²,

Noah³

et al. 2012

JOKM

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Systems that help to find answers to suitable experts have received the attention of many researchers. Pioneer researchers on the development of search system for experts emphasized the importance of a search system that required returning a list prioritizing the names of individuals. Among the issues raised related to locating experts are, the critical problem of maintaining up-todate information in the expert database and the inadequacy in expert finding systems in returning search results that are expected to account for not only the list of the names of the experts, but any information related to the experts and those involved with them. In the last decade, researchers have examined the search for experts from various research perspectives such as expert tracking system and construction of expert profiles involving ontology. This paper aims to describe a new approach in designing a framework for the construction of ontology that will be used in the directory of ICT experts. The researchers propose to incorporate thesaurus in their construction of ontology on ICT experts by providing a profile of the experts including their social profile and whatever concerns that may be associated with the expert. The researchers constructed the ontology on ICT experts by extracting information from sources such as their resumes and personal web sites to obtain the index glossary of words that characterized experts to be used in the directory of experts system. In this study, the standards contained in the Performance Evaluation System of the National University of Malaysia are used to extract information on the academicians in the Faculty of Information Science and Technology. The researchers employed the index glossary, metadata of experts and integrate appropriate taxonomy, thesaurus and classification schemes; such as Association for Computing Machinery (ACM) taxonomy, web classification schemes such as Standard Industrial Classification (SIC), North American Industry Classification System (NAICS) to enrich the ontology of ICT expertise. The proposed framework aims at helping users find information on the expert they require and at the same time obtain other information related to the experts from various perspectives encompassing research, consultancy, links with research partners, other interest related to a particular field and other resources. With a semantically driven directory of ICT experts, matters related to ICT can be referred to the right experts. The framework will be validated by developing the directory of ICT experts prototype and by involving domain experts to evaluate the content of the ontology constructed. In addition, the researchers will evaluate the search results of users who will use the prototype to search for ICT experts.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Expert Tracking Systemmentioning

confidence: 99%

Section: Journal Of Organizational Knowledge Managementmentioning

confidence: 99%

Section: Journal Of Organizational Knowledge Managementmentioning

confidence: 99%

Section: Journal Of Organizational Knowledge Managementmentioning

confidence: 99%

See 3 more Smart Citations

A Framework for the Construction of Ontology for ICT Experts

Aris¹,

Salim²,

Noah³

et al. 2012

JOKM

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Integrating multiple windows and document features for expert finding

Zhu

Song

Rüger

2009

J. Am. Soc. Inf. Sci.

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Expert finding is a key task in enterprise search and has recently attracted lots of attention from both research and industry communities. The Text REtrieval Conference 2 (TREC) has organized an expert search task for 2005, 2006, and 2007. Given a search topic, a prominent existing approach is to apply some information retrieval (IR) system to retrieve top ranking documents, which will then be used to derive associations between experts and the search topic based on co occurrences. However, we argue that expert finding is more sensitive to multiple document features that current expert finding systems insufficiently address, including: (1) multiple levels of associations between experts and search topics, (2) document internal structure and (3) document authority. We propose a novel approach which integrates the above three aspects as well as a query expansion technique in a two stage model for expert finding. A systematic evaluation is conducted on the TREC2006 and TREC2005 expert search collections to test the performance of our approach and the effects of different aspects of document features and query expansion. These experimental results show that query expansion can dramatically improve expert finding performance.Both document internal structure and our novel multiple window based approach for taking into account multiple levels of associations improve expert finding over the direct use of a number of well known IR models for both with and without query expansion. KeywordsExpert finding, enterprise search 1 Correspondence author.

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