Enhanced SPARQL-based design rationale retrieval

Abstract

Design rationale (DR) is an important category within design knowledge, and effective reuse of it depends on its successful retrieval. In this paper, an ontology-based DR retrieval approach is presented, which allows users to search by entering normal queries such as questions in natural language. First, an ontology-based semantic model of DR is developed based on the extended issue-based information system-based DR representation in order to effectively utilize the semantics embedded in DR, and a database of ontology-based DR is constructed, which supports SPARQL queries. Second, two SPARQL query generation methods are proposed. The first method generates initial SPARQL queries from natural language queries automatically using template matching, and the other generates initial SPARQL queries automatically from DR record-based queries. In addition, keyword extension and optimization is conducted to enhance the SPARQL-based retrieval. Third, a design rationale retrieval prototype system is implemented. The experimental results show the advantages of the proposed approach.

Performance Analysis for the Ontology based Intelligent Information Retrieval using Non Monotonic Inference Logic using SPARQL

“…At one end, it enables the system to represent its resources by semantically annotating them and later storing them in a structured manner. On the other end, it provides machine readable learner profiling and querying the agent (SPARQL) which helps to visualize the user's current needs precisely (Li et al, 2016).…”