Survey on the Applications of the Graph Theory in the Information Retrieval
Subject Areas : Information and Knowledge Technology
Maryam Piroozmand
1
(Faculty of Engineering Science, Faculty of Engineering, University of Tehran, Iran)
Amir Hosein Keyhanipour
2
(Computer Engineering Department, Faculty of Engineering, College of Farabi, University of Tehran, Iran)
Ali Moeini
3
(Faculty of Engineering Science, Faculty of Engineering, University of Tehran, Iran)
Keywords: Graph Theory, Information Retrieval, Learning to Rank, Knowledge Graph, Graph-based Dataset Representation,
Abstract :
Due to its power in modeling complex relations between entities, graph theory has been widely used in dealing with real-world problems. On the other hand, information retrieval has emerged as one of the major problems in the area of algorithms and computation. As graph-based information retrieval algorithms have shown to be efficient and effective, this paper aims to provide an analytical review of these algorithms and propose a categorization of them. Briefly speaking, graph-based information retrieval algorithms might be divided into three major classes: the first category includes those algorithms which use a graph representation of the corresponding dataset within the information retrieval process. The second category contains semantic retrieval algorithms which utilize the graph theory. The third category is associated with the application of the graph theory in the learning to rank problem. The set of reviewed research works is analyzed based on both the frequency as well as the publication time. As an interesting finding of this review is that the third category is a relatively hot research topic in which a limited number of recent research works are conducted.
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