Measuring the Similarity between TV Programs using Semantic Relations

This paper presents a novel method of measuring the similarity between TV programs by using summaries of the Electronic Program Guide (EPG). Most previous methods use statistics such as the TFIDF based cosine measure of word vectors, whose elements are words appearing in the summaries. However, these approaches are not effective because TV program summaries, especially short ones, do not necessarily share many words even when they have similar meanings. The proposed method generates a graph structure whose nodes are TV programs and nouns. These nouns are connected by semantic relations that are extracted from the Web automatically. The similarity between two TV programs is measured in terms of the relativeness of two TV program’s nodes in the graph structure by using a random walk algorithm. Experiments showed that our method is better at measuring similarities between two TV programs compared with baseline methods.