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In this paper we propose a hybrid method of literature recommendation in the academic community. First, we refer the objective recommendation based on HITS algorithm by constructing a directed graph according to the literature citation relation and then select the articles considering the authority and hub score of each article synthetically and add them to the recommendation list. This can narrow the recommendation scope and give a more authoritive recommendation. Second, the subjective recommendation is based on collaborative filtering by comparing the ratings of other similar users for the objects in recommendation list. The difference is we discover the similar user by clustering them. And the experiment shows the method can provide better recommendation results and is timesaving.

Clustering web search results is a kind of solution which help user to find the interested topic by grouping the search results. This paper presents an improved method for clustering search results focused on Chinese web pages. The main contributions of this paper are the following: First, in this paper, a method which identifies the complete semantic information phrase by comparing the attributes of base clusters in the suffix tree document model and the overlap of their document sets is presented. Second, by analyzing the content and structure of title and snippet of Chinese web search results, one way of sentence segmentation is designed and implemented to constructing suffix tree. Third, In order to better respond to the associate degree of terms, a novel method is proposed which compute the distance in sentence-grain of terms' co-occurrences. Finally, the experiment illustrates that the new clustering method provides an efficient and effective way for user browsing and locating sought information.

The method of merging concept lattice in domain ontology construction can describe the implicit concepts and relationships between concepts more appropriately for semantic representation and query match. In order to enrich semantic query, the paper intends to apply the theory of Formal Concept Analysis (FCA) to establish source concept lattices, through which the domain concepts are extracted from source concept lattices to generate the optimized concept lattice. Then, the ontology tree is generated by lattice mapping ontology algorithm (LMOA) combing some hierarchical relations in the optimized concept lattice. The experiment proves that the domain ontology can be achieved effectively by merging concept lattices and provide the semantic relations more precisely.

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