Earticle

초록

영어

Building large relevance datasets is important for the training and evaluation of Information Retrieval (IR) systems. This process involves the collection of documents, queries and assessors' judgments of the degree of relevance of a query to a document. This process is expensive and time consuming. Additionally, it is not a one-of-a-kind project as it can be repeated for different languages and different corpora scopes and with different techniques. This paper presents a software engineering solution for the process of creating relevance corpora that achieves reusability, flexibility, multilingualism and modularity, in order to respect the experimental nature of IR field. The software engineering solution is presented as UML models. This paper then shows how the proposed design model was used to implement the process of building an open source relevance Arabic corpus based on the Clue Web 2009 data set for the purpose of supporting research evaluating and improving search engines for Arabic language.

목차

Abstract
 1. Introduction
 2. Literature Review
  2.1. Documents:
  2.2 Queries:
  2.3. Judgment:
 3. Software Engineering Solution for Creating Relevance Corpus
  3.1. Design Goals
  3.2. Object Oriented Models
 4. Implementation
 5. Conclusions and Future Work
 References

키워드

저자

• Nuha H. El-Khalili [ Faculty of Information Technology, University of Petra, Amman, Jordan ]
• Bassam Haddad [ Faculty of Information Technology, University of Petra, Amman, Jordan ]
• Haya El-Ghalayini [ Faculty of Information Technology, University of Petra, Amman, Jordan ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Software Engineering and Its Applications

• 간기

  월간

• pISSN

  1738-9984

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605