Retrieve and Rank the Experts Using a Cluster-based Translation Model

Q: How can I download an article?

To download an article from SID, first log in to the site, search for the article title, and click on the 'Download Article' option.

Q: How can I download an ISI article?

To download an ISI article on SID, enter the keyword or article title in the search bar, view the relevant results, click on the desired article, and select the 'Download Article' option.

Q: How can I access the SID database?

To access the SID database, visit SID.ir, create an account, and log in to access scientific resources.

Q: Is downloading articles from SID free?

Some articles on SID are available for free, while others require payment. Details are specified on the article's page.

DEHGHAN MAHDI; Abin Ahmad Ali

مرکز اطلاعات علمی Scientific Information Database (SID) - Trusted Source for Research and Academic Resources

Journal Paper

Paper Information

Journal: TABRIZ JOURNAL OF ELECTRICAL ENGINEERING Year:2019 | Volume:49 | Issue:3 (89) Page(s): 1095-1106

Download Full-Text

Persian Verion

View:

588

Download:

Cites:

Information Journal Paper

Title

Retrieve and Rank the Experts Using a Cluster-based Translation Model

Author(s)

DEHGHAN MAHDI | Abin Ahmad Ali | Issue Writer Certificate

Keywords

Expertise retrievalQ1

translation modelQ1

question answering systemsQ2

topic modelingQ1

vocabulary gapQ1

Abstract

With respect to the increasing volume and variety of information available on the Web, it is very difficult to find the required knowledge through the massive amount of data. Question-answering systems have been created to make easy knowledge accessing through massive amounts of data. The most important factor in the issue of expert finding is the ability to detect the relationship between query words and documents written by the candidate experts. A challenging issue in this area is the vocabulary gap between query words and the documents of the candidate experts. In this paper, two new translation models are proposed to solve the problem of the vocabulary gap. First model, a cluster-based probabilistic model, and another is based on topic modeling. In these models, the query words are translated into a collection of query-related words, which are written in documents written by more candidate experts. Then, using these words and using a simple composite model, we have retrieved the experts. The proposed models are implemented and evaluated on the Stack overflow test set and finally, we have analyzed the outputs. The results indicate an increase in the Mean Average Precision of the proposed method compared with other methods of expert finding.

Cites

No record.

References

No record.

Cite

APA: Copy

DEHGHAN, MAHDI, & Abin, Ahmad Ali. (2019). Retrieve and Rank the Experts Using a Cluster-based Translation Model. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, 49(3 (89) ), 1095-1106. SID. https://sid.ir/paper/372035/en

Vancouver: Copy

DEHGHAN MAHDI, Abin Ahmad Ali. Retrieve and Rank the Experts Using a Cluster-based Translation Model. TABRIZ JOURNAL OF ELECTRICAL ENGINEERING[Internet]. 2019;49(3 (89) ):1095-1106. Available from: https://sid.ir/paper/372035/en

IEEE: Copy

MAHDI DEHGHAN, and Ahmad Ali Abin, “Retrieve and Rank the Experts Using a Cluster-based Translation Model,” TABRIZ JOURNAL OF ELECTRICAL ENGINEERING, vol. 49, no. 3 (89) , pp. 1095–1106, 2019, [Online]. Available: https://sid.ir/paper/372035/en

Related Journal Papers