Abstract
AbstractSemantic Associations are complex relationships between entities over metadata represented in a RDF graph. While searching for complex relationships, it is possible to find too many relationships between entities. Therefore, it is important to locate interesting and meaningful relations and rank them before presenting to the end user. In recent years e-learning systems have become very popular in all fields of higher education. In an e-learning environment, user may expect to search the semantic relationship paths between two concepts or entities. There may be numerous relationships between two entities which involve more intermediate entities. In order to filter the size of results set based on user's relevance, user may introduce one or more known intermediate entities. In this paper, we present a Modified bidirectional Breadth-First-Search algorithm for finding paths between two entities which pass through other intermediate entities and the paths are ranked according to the users' needs. We have evaluated our system through empirical evaluation. We have compared the execution time to discover the paths between entities for our proposed search method and existing method. According to our experiments our proposed algorithm improves search efficiently. The average correlation coefficient between the proposed system ranking and the human ranking is 0.69. It explains that our proposed system ranking is highly correlated with human ranking.
Highlights
Information retrieval over semantic metadata [1] has received a great amount of interest in both industry and academia
The Resource Description Framework (RDF)[3] data model provides a framework to capture the meaning of an entity by specifying how it relates to other entities
A semantic association is a set of relationships between two entities in a knowledge base represented as graph paths consisting of a sequence of links
Summary
Information retrieval over semantic metadata [1] has received a great amount of interest in both industry and academia. How person ‘X’ is related to person ‘Y’ To answer this question, we need to find the semantic association paths between person ‘X’ and person ‘Y’. Person ‘X’ may be related to person ‘Y’ with one or more intermediate entities, the results may be too large depending on the size of the RDF graph and most of the relationships may be irrelevant to the user. User wants to find the relationship paths between person ‘X’ and person ‘Y’ with respect to person ‘Z’, he/she can introduce ‘Z’ as intermediate entity to find the paths. We propose a Modified Bidirectional Breadth-First-Search algorithm to discover the paths between two entities which pass through user-specific intermediate entities.
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