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A new semi-supervised approach for Chinese relation extraction (RE) over constantly growing and edgeless web data is introduced in this paper. Existing semi-supervised approaches have the better improvement potential while lacking syntactic structure and semantic meaning of a sentence and unsuitable to loosely structured Chinese sentences. To follow their basic procedures as well as covering their...
With the development of mobile technology, Internet and GIS, LBS plays an important role in various applications. As the basis of LBS, the research on acquisition, processing, storage, query of mobile object trajectories has been quite mature, but the analysis and the application of movement patterns contained in mobile object trajectories is relatively lagging behind. The calculation of trajectory...
Sequential pattern mining based on constraint is now an important research direction of data mining, since it can reduce the generation of useless candidates as well as make the generated patterns meet the requirements of special users. Average value constraint is a kind of tough aggregate constraint. We propose here an effective pruning strategy based on average value constraint to avoid constructing...
Recommender system emerges as a technology addressing "information overload" problem. Collaborative Filtering (CF) is successful and widely used in many personalized recommender applications, such as digital library, e-commerce, news sites, and so on. However, most collaborative filtering algorithms suffer from data sparsity problem which leads to inaccuracy of recommendation. This paper...
In this paper, we propose a new measure framework for evaluating taxonomy relationships in ontologies using lexical semantic relatedness. First, we suggest a new quantitative measure model for WordNet, the model can be used to compute the semantic relatedness of concepts in ontologies. Next, according to the relativities of concepts, we describe the way to estimate the classification consistency of...
Collaborative filtering (CF) is one of the most successful technologies in recommender systems, and widely used in many personalized recommender applications, such as digital library, e-commerce, news sites, and so on. However, most collaborative filtering algorithms suffer from data sparsity problem which leads to inaccuracy of recommendation. This paper is with an eye to missing data imputation...
Analyzing existing location modeling, this paper addresses location issues in ubiquitous mobile computing and presents a semantic location model, which introduces query and context semantics into this user-centered model, to support context-awareness based cooperative mobile event. An event-reasoning mechanism, based on semantic matching, is established to recognize and make use of semantics. A natural...
This paper presents an automatic term extraction method based on Markov process. The method aims to extract multi-word domain terms from English corpora. The paper proves that the extracting term process is a Markov chain firstly, and then gives the steps of the Markov-based method. In order to evaluate our method, we use a corpus related to computer science got by Web crawlers, and extract domain...
A new method to compute the similarity of two blog posts is proposed in this paper. This method mainly has two parts including keywords extraction and semantic similarity measurement. During keywords extraction part, the method utilizes particular post features to extract keywords from one blog post with the aim to improve the correlation rate. In order to compute the similarity of any two blog posts...
This paper presents a method of extracting domain ontology from WordNet. The novelty of the method is taking WordNet as one and only knowledge base, this can improve the efficiency of domain ontology building. In our method, kernel concepts are given by domain experts firstly, then IC-based semantic similarity algorithm is used to extract domain concepts from WordNet, in the end, domain concepts are...
Information Content (IC) is an important dimension of assessing the semantic similarity between two terms or word senses in word knowledge. The conventional method of obtaining IC of word senses is to combine knowledge of their hierarchical structure from an ontology like WordNet with actual usage in text as derived from a large corpus. In this paper, a new model of IC is presented, which relies on...
The openness of Internet leads to security problems of network, among which content security is an important problem. In order to solve the problem effectively, a security scheme of information content which based on content security ontology (CSO) is presented. CSO is extracted from a security kernel (SK) which is a lexicon of information security knowledge drawing out from general thesaurus and...
Blog post summarization using fast features facilitates users' quick browsing through blog search results. Much existing research on blogs ignores blog tags and text structure. In this paper, we re-formalize the blog post summarization problem as a sentence extraction and sentence ranking problem. Three fast features, important sentences, blog tags and blog comments, are proposed to calculate salience...
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