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. Simultaneously, it generates a personal context-aware dictionary dynamically from the keywords gotten via some APIs in the Internet. Currently, the information of user's context is also provided by NGN. In this paper, we explain the overview of our proposal and prototype implementation in Japanese.
based on ontology. It uses the rich semantic knowledge of ontology to upgrade the retrieval based on keywords to concepts, and combines it with the specialized engine to improve retrieval effect and efficiency. The paper also takes patent information for example to explain its application at the end.
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
, emotion keywords which behave distributions of 3D structure can be projected into the emotion space. Emotion distributions were transformed into an emotion matrix. By analyzing the emotion matrix, not only binary classification of texts but also multi-emotion attributes can be investigated. The best precision 91% of a binary
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.
semantic lexicon for domain-specific term extraction. The experimental results show that our approach can get high precision in legal field. Keywords: automatic term recognition, bilingual seeds set, Chinese concept dictionary, legal terminology, single word term.
Many language-oriented problems cannot be solved without semantic memory containing descriptions of concepts at different level of details. Automatic creation of semantic memories is a great challenge even for the simplest knowledge representation methods based on relations between concepts and keywords. Semantic
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.