Program recommending apparatus and method

Abstract

The invention relates to a program recommendation apparatus and method. The apparatus includes: a module configured to extract category information and program abstracts of programs contained in an electronic program guide, extract program-specific terms from the program abstracts by morphological analysis and combine the category information and the program-specific terms to generate category-added terms; a module configured to analyze a history of programs viewed by a user based on the generated category-added terms to generate a preference vector indicating user's preferences for programs; a module analyzing the program abstracts based on the category-added terms to generate broadcast program vectors; a module generating a relevant term model for the category-added terms; a module calculating similarities between the preference vector and each of the broadcast program vectors based on the generated relevant term model; and a module outputting programs having the calculated similarities satisfying a predetermined condition as recommended programs matching with the user's preferences.

Description

[0001] Cross References to Related Applications [0002] The present invention relates to subject matter contained in Japanese Patent Application No. 2008-056540 filed Mar. 3, 2008, which is hereby incorporated by reference in its entirety. technical field [0003] The invention relates to a program recommending device and program recommending method for recommending TV programs to users. Background technique [0004] Since the number of programs has increased in recent years, it has become more difficult for users to search for favorite programs. In view of this situation, there is an increasing demand for program recommendation systems. The system learns user preferences from the user's history of programs watched, and recommends programs that the user likes. [0005] Program information has been digitized as an Electronic Program Guide (EPG). A system has been proposed that recommends programs by using text information such as genres, actors, and program summaries cont...

AI Technical Summary

Problems solved by technology

Although programs containing the word "news" or "information" are recommended, it is difficult to specify a recommended program because the word is included in many programs

Recommending all programs that contain the word "news" or "information" results in very low recommendation accuracy

[0012] The second problem is that the context in which the word occurs is not considered at all in the background technology approach

Although it is clear that the words associated with "travel" in animated shows are different from the words associated with "travel" in travel variety shows, these associated words cannot be distinguished by direct use of the word "travel"

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