Discovering Intelligent Agent: A Tool for Helping Students Searching a Library

Yammine, Kamal; Razek, Mohammed Abdel; Aïmeur, Esma; Frasson, Claude

doi:10.1007/978-3-540-30139-4_68

Cited by 5 publications

(3 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It is found that for user 3,8,11,13,14, and 15 all relevant concepts are get retrieved. For those users profile agent retrieved almost all right keywords to update the user profiles.…”

Section: Discussionmentioning

confidence: 96%

See 1 more Smart Citation

Identifying subject area/s of user using n-Gram and Jaccard's similarity in profile agent of library recommender system

Shirude

Kolhe

2014

Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies

View full text Add to dashboard Cite

The proposed framework of the library recommender system includes implementation of three agent viz. profile agent, content based agent, and collaborative agent. One of the important tasks performed by profile agent is the identification of subject area/s of user. The implementation of this part is focused in this paper. This work uses n-Gram and Jaccard's similarity. The ACM's Computing Classification System is used as knowledgebase. This is required to be used while deciding in which subject area/s the particular user may have interests. This work is essential to be performed in implementation of library recommender system. The output of this work is used by the library recommender agent (content based and collaborative). The results are evaluated using precision, recall, and F-1 measure. Comparison with similar work identified during literature study is done. It is found that n-Gram and Jaccard's similarity are useful and gives better performance for the particular task implemented in profile agent.

show abstract

“…It is found that for user 3,8,11,13,14, and 15 all relevant concepts are get retrieved. For those users profile agent retrieved almost all right keywords to update the user profiles.…”

Section: Discussionmentioning

confidence: 96%

“…Users of library are of different backgrounds. They are not able to get the right resources at the right time [3]. Artificial Intelligence and machine learning techniques can be useful to obtain the way to handle such large amount of resources in library [4].…”

Section: Introductionmentioning

confidence: 99%

Identifying subject area/s of user using n-Gram and Jaccard's similarity in profile agent of library recommender system

Shirude

Kolhe

2014

Proceedings of the 2014 International Conference on Information and Communication Technology for Competitive Strategies

View full text Add to dashboard Cite

show abstract

“…Only two operations are available: passing the learning-style test or disconnecting from the system (see Figure 5). According to [Yammine et al 2004], the learning-style test consists of questions. The IECA uses the answers to identify a specific the learning style.…”

Section: Learning-style Testmentioning

confidence: 99%

The Pyramid Collaborative Filtering Method: Toward an Efficient E-Course

Kiared

Razek

Frasson

2006

Intelligent Tutoring Systems

Self Cite

View full text Add to dashboard Cite

Web-based applications with very diverse learners fail because they fail to satisfy various needs. Some people use collaborative filtering methods to analyze learners' profiles and provide recommendation to a new learners, but this methods provides false recommendations from beginners. We present a new method, which provides recommendations that depend on the credibility rather than the number of learners. We have designed, implemented, and tested what we call the Intelligent E-Course Agent (IECA). Our evaluation experiment shows that our approach greatly improves learners' knowledge and therefore presents a course that is more closely related to their needs.

show abstract

Classification of Library Resources in Recommender System Using Machine Learning Techniques

Shirude¹,

Kolhe²

2018

Social Transformation – Digital Way

View full text Add to dashboard Cite

Discovering Intelligent Agent: A Tool for Helping Students Searching a Library

Cited by 5 publications

References 16 publications

Identifying subject area/s of user using n-Gram and Jaccard's similarity in profile agent of library recommender system

Identifying subject area/s of user using n-Gram and Jaccard's similarity in profile agent of library recommender system

The Pyramid Collaborative Filtering Method: Toward an Efficient E-Course

Classification of Library Resources in Recommender System Using Machine Learning Techniques

Contact Info

Product

Resources

About