RECOMMENDATION METHOD AND RECOMMENDER COMPUTER SYSTEM USING DYNAMIC LANGUAGE MODEL
First Claim
1. A recommendation method using dynamic language model, comprising:
- providing one or a plurality of sentences by at least a computer peripheral device, wherein the one or a plurality of sentences comprises a plurality of words;
analyzing a plurality of word occurrence probabilities of the one or a plurality of sentences by at least an electric element;
analyzing a plurality of word continuation probabilities among the words by at least an electric element;
constructing one or a plurality of language models according to the word occurrence probabilities and the word continuation probabilities by at least an electric element;
emerging the one or a plurality of language models to construct a dynamic language model by at least an electric element;
providing a search keyword to generate a plurality of recommended sentences by search process according to the search keyword by at least a computer peripheral device;
analyzing a difference level between each of the recommended sentences and the dynamic language model in terms of the word occurrence probabilities and the word continuation probabilities so as to generate a plurality of difference levels by at least an electric element; and
sorting the recommended sentences according to the difference levels to provide a recommendation list by at least an electric element.
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Abstract
A recommendation method and a recommender computer system using dynamic language model are provided. The recommender computer system using dynamic language model includes a language model constructing computer module, a language model adapting computer module, a sentence selecting computer module and a sentence recommendation computer module. The language model constructing computer module is used for constructing a language model. The language model adapting computer module is used for dynamically emerging different language models to construct a dynamic language model. The sentence selecting computer module generates a plurality of recommended sentences from a database according to a search keyword. The sentence recommendation computer module analyzes the difference level between the recommended sentences and the dynamic language model and sorts recommended sentences to provide a recommendation list.
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Citations
17 Claims
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1. A recommendation method using dynamic language model, comprising:
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providing one or a plurality of sentences by at least a computer peripheral device, wherein the one or a plurality of sentences comprises a plurality of words; analyzing a plurality of word occurrence probabilities of the one or a plurality of sentences by at least an electric element; analyzing a plurality of word continuation probabilities among the words by at least an electric element; constructing one or a plurality of language models according to the word occurrence probabilities and the word continuation probabilities by at least an electric element; emerging the one or a plurality of language models to construct a dynamic language model by at least an electric element; providing a search keyword to generate a plurality of recommended sentences by search process according to the search keyword by at least a computer peripheral device; analyzing a difference level between each of the recommended sentences and the dynamic language model in terms of the word occurrence probabilities and the word continuation probabilities so as to generate a plurality of difference levels by at least an electric element; and sorting the recommended sentences according to the difference levels to provide a recommendation list by at least an electric element. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A recommender computer system using dynamic language model, comprising:
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a language model constructing computer module used for analyzing a plurality of word occurrence probabilities of a plurality of words of one or a plurality of sentences and a plurality of word continuation probabilities among the words, and constructing one or a plurality of language models according to the word occurrence probabilities and the word continuation probabilities by at least an electric element; a language model adapting computer module comprising an adapting unit for constructing a dynamic language model according to the one or a plurality of language models by at least an electric element; a sentence selecting computer module used for generating a plurality of recommended sentences from a database containing one or a plurality of sentences by a search process according to a search keyword by at least an electric element; and a sentence recommendation computer module used for analyzing the difference level between each of the recommended sentences and the dynamic language model in terms of the word occurrence probabilities and the word continuation probabilities so as to generate a plurality of difference levels and sort the recommended sentences according to the difference levels to provide a recommendation list by at least an electric element. - View Dependent Claims (9, 10, 11, 12, 13, 14, 15, 16, 17)
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Specification