INFORMATION RECOMMENDATION DEVICE AND INFORMATION RECOMMENDATION METHOD
First Claim
1. An information recommendation device, comprising:
- a document input unit which inputs a document set of which each document has date and time information within a specified time period;
a document analysis unit which obtains a plurality of characteristic vectors each including a plurality of keywords of vector elements by each keyword analyses of the document set or history documents including browsed documents or documents labeled by bookmark operations;
a clustering unit which obtains a plurality of topic clusters and a plurality of sub-topic clusters which are each composed of documents belonging to the same topic by clustering the document set;
a topic transition generation unit which generates a transition structure showing transitions of topics among the sub-topic clusters;
a characteristic attribute extraction unit which extracts a characteristic attribute of frequently included keyword from each topic cluster and each sub-topic cluster;
a cluster-of-interest extraction unit which extracts a cluster-of-interest equivalent to any one of the plurality of topic clusters or sub-topic clusters by similarity determination among the characteristic vectors of history documents and the characteristic vector of each document included in the document set;
a recommended document extraction unit which obtains a sub-topic cluster having transition relations with the cluster-of-interest on the basis of the transition structure owned by the cluster-of-interest, and extracts a document included in the sub-topic cluster as a recommended document; and
a recommended document presentation unit which presents the recommended document together with the characteristic attribute.
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Accused Products
Abstract
A document set, and history documents including documents, etc., browsed by a user are input. The document set and the history documents are each analyzed to obtain characteristic vectors. A plurality of topic clusters and a plurality of sub-topic clusters are obtained by clustering the document set. A transition structure showing transitions of topics among the sub-topic clusters is generated, and a characteristic attribute is extracted from each topic cluster and each sub-topic cluster. An cluster-of-interest is extracted in comparison among characteristic vectors of the history documents and a characteristic vector of each document included in the document set, a sub-topic cluster having transition relations with the cluster-of-interest is obtained on the basis of a transition structure owned by the cluster-of-interest, and a document included in the sub-topic cluster is extracted as a recommended document to be presented together with the characteristic attribute.
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Citations
19 Claims
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1. An information recommendation device, comprising:
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a document input unit which inputs a document set of which each document has date and time information within a specified time period; a document analysis unit which obtains a plurality of characteristic vectors each including a plurality of keywords of vector elements by each keyword analyses of the document set or history documents including browsed documents or documents labeled by bookmark operations; a clustering unit which obtains a plurality of topic clusters and a plurality of sub-topic clusters which are each composed of documents belonging to the same topic by clustering the document set; a topic transition generation unit which generates a transition structure showing transitions of topics among the sub-topic clusters; a characteristic attribute extraction unit which extracts a characteristic attribute of frequently included keyword from each topic cluster and each sub-topic cluster; a cluster-of-interest extraction unit which extracts a cluster-of-interest equivalent to any one of the plurality of topic clusters or sub-topic clusters by similarity determination among the characteristic vectors of history documents and the characteristic vector of each document included in the document set; a recommended document extraction unit which obtains a sub-topic cluster having transition relations with the cluster-of-interest on the basis of the transition structure owned by the cluster-of-interest, and extracts a document included in the sub-topic cluster as a recommended document; and a recommended document presentation unit which presents the recommended document together with the characteristic attribute. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9)
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10. An information recommendation method, comprising:
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inputting a document set of which each document has date and time information within a specified time period; obtaining a plurality of characteristic vectors which each include a plurality of keywords of vector elements by each keyword analyses of the document set or history documents including browsed documents or documents labeled by bookmark operations; obtaining a plurality of topic clusters and a plurality of sub-topic clusters which are each composed of documents belonging to the same topic by clustering the document set; generating a transition structure which shows transitions of topics among the sub-topic clusters; extracting a characteristic attribute from each topic cluster and each sub-topic cluster; extracting a cluster-of-interest equivalent to any one of the plurality of topic clusters or sub-topic clusters by similarity determination among characteristic vectors of the history documents and characteristic vector of each document included in the document set; obtaining a sub-topic cluster which has transition relations with the cluster-of-interest on the basis of the transition structure owned by the cluster-of-interest, and extracting a document included in the sub-topic cluster as a recommended document; and presenting the recommended document together with the characteristic attribute. - View Dependent Claims (11, 12, 13, 14, 15, 16, 17, 18)
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19. An information recommendation program stored in a computer readable medium, the program comprising:
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document input means for instructing a computer to input a document set of which each document has date and time information within a specified time period; document analysis means for instructing the computer to obtain a plurality of characteristic vectors each including a plurality of keywords of vector elements by each keyword analyses of the document set or history documents including browsed documents or documents labeled by bookmark operations; clustering means for instructing the computer to obtain a plurality of topic clusters and a plurality of sub-topic clusters which are each composed of documents belonging to the same topic by clustering the document set; topic transition generation means for instructing the computer to generate a transition structure showing transitions of topics among the sub-topic clusters; characteristic attribute extraction means for instructing the computer to extract a characteristic attribute of frequently included keyword from each topic cluster and each sub-topic cluster; cluster-of-interest extraction means for instructing the computer to extract a cluster-of-interest equivalent to any one of the plurality of topic clusters or sub-topic clusters by similarity determination among the characteristic vectors of the history documents and the characteristic vector of each document included in the document set; recommended document extraction means for instructing the computer to obtain a sub-topic cluster having transition relations with the cluster-of-interest on the basis of the transition structure owned by the cluster-of-interest, and extract a document included in the sub-topic cluster as a recommended document; and recommended document presentation means for instructing the computer to present the recommended document together with the characteristic attribute.
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Specification