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This paper proposes a structure that automatically analyzes the parameters of Chinese test items. This structure utilizes latent semantic analysis (LSA) to analyze the relationships of keywords among all test items in an item bank. It also uses the similarity measure to calculate the similarity degree of keywords. We
relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison
We introduce a new method for discovering latent topics in sets of objects, such as documents. Our method, which we call PARIS (for Principal Atoms Recognition In Sets), aims to detect principal sets of elements, representing latent topics in the data, that tend to appear frequently together. These latent topics, which we refer to as `atoms', are used as the basis for clustering, classification, collaborative...
Research on cross-language information retrieval (CLIR) increasingly concentrates in candidate translation selection of the keywords in the query. The accuracy of translation has a direct impact on accurate rate and recalled rate. This thesis presents three methods based on HowNet to resolve query translation
The abounded keywords, which were active jamming in Chinese, induced a mass of malicious Web pages in network content security fields. These keywords were distorted with homophones or complexity characters to replace one of the character or with punctuations random jamming and so on. The conventional pattern matching
Arabic. That motivates the author to build a repository and its retrieval system for collection of al Hadith in the Indonesian language. The retrieval of document used Nazief and Andriani stemming algorithms with the programming language PHP to display the search results based on the keywords entered by the user and an XML
, irrelevant tweets were further segregated by means of a unigram dictionary containing education-oriented keywords. The Apriori algorithm was then applied to the dataset thus obtained resulting in characteristic markers or patterns of these institutes.
overall life time. The "bag-of-words" model is used to represent the content of an article as a vector of features, which are uni-, bi-, or tri-gram keywords. The thesaurus approach is applied to group words with similar meanings to a set of root words to reduce the size of the feature space. Normalized TF-IDF
is to stem and eliminate common words. The aim of this research is to stem words from Persian documents to make their use more efficient in text summarization, the present method is to eliminate words and stem keywords. The compound of existing techniques in the words network was used to create a Persian database using
a series of Keywords. The main focus of this paper lies with matching of standard questions and questions asked by users. An experimental system based on the proposed method has been built, and the results of our experiments shows the proposed method is effective for question matching.
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