Authors:
Damiano Distante
1
;
Luigi Cerulo
2
;
Aaron Visaggio
2
and
Marco Leone
2
Affiliations:
1
Unitelma Sapienza University, Italy
;
2
University of Sannio, Italy
Keyword(s):
Discussion Forums, Navigability, Searchability, Information Search, Information Extraction, Text Mining, Topic Modeling, e-Learning, Learning Management Systems.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Concept Mining
;
Information Extraction
;
Interactive and Online Data Mining
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining Text and Semi-Structured Data
;
Symbolic Systems
Abstract:
One of the most popular means of asynchronous communication and most rich repository of user generated information over the Internet is represented by online discussion forums. The capability of a forum to satisfy users’ needs as an information source is mainly determined by its richness in information, but also by the way its content (messages and message threads) is organized and made navigable and searchable. To ease content navigation and information search in online discussion forums we propose an approach that introduces in them a complementary navigation structure which enables searching and navigating forum contents by topic of discussion, thus enabling a topic-driven navigational paradigm. Discussion topics and hierarchical relations between them are extracted from the forum textual content with a semi-automatic process, by applying Information Retrieval techniques, specifically Topic Models and Formal Concept Analysis. Then, forum messages and discussion threads are associa
ted to discussion topics on a similarity score basis. In this paper we present an implementation of our approach for the Moodle learning management system, opening to the application of the approach to several real e-learning contexts. We also show with a case study that the new topic-driven navigation structure improves information search tasks with respect to using Moodle standard full-text search.
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