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Most of the mobile platforms provide a keyword based full text search (FTS) for users to find what they want. However, FTS has difficulties in dealing with the cases where a user cannot remember the exact keywords about target data or the number of search results is too many. To overcome these limitations of FTS, we
Due to the huge number of research articles in the biomedical domain, it becomes more and more important to develop methods to find relevant articles of our specific research interests. Keyword extraction is a useful method to find important topics from documents and summarize their major information. Unfortunately
Traditional information gathering systems are mostly keyword-based that are lack of semantic comprehension and analysis ability and can't guarantee the comprehensiveness and accuracy of information gathering. This paper proposes Chinese patent information gathering model based on domain ontology, which can visualize
In the era of information explosion, information retrieval has become a bottleneck in information sharing and integration. However currently, the existing information retrieval methods are mainly based on keyword matching, which can not fully take advantage of the information context and potential knowledge. All of
In recent years, the application of ontology has been already toward the diversification under the development of the semantic Web technology. The main application of ontology is information retrieval. With the utilization of ontology, we expect to offer more correct information for users. Although, most of the applications of ontology are information retrieval but they lacks of the interaction with...
paper proposed a new architecture (a keyword based approach) to recognize emotions from text. In case of recognizing emotion from a piece of text document or a blog, any human can do this better than a machine only problem is he/she takes time. Proposed emotion detector system takes a text document and the emotion word
This paper proposes a novel personalized news recommendation system named InfoSlim. The new system uses semantic technique to annotate news items and user preference in order to add rich metadata information into traditional keyword vector. By doing this, the similarity measure between item profile and user profile
Spatial information retrieval which is mainly catalog service based on metadata is the foundation of spatial information sharing. Today's information retrieval methods in catalog service are typically limited to keyword searches or matches of sub-strings, which do not meet user's retrieval demand. This paper presents
Our research addresses semantic retrieval of images from plethora of image dumps by imparting human cognition in the image retrieval process. Proposed architecture SIREA addresses the issues of keyword based image retrieval and content based image retrieval through semantics. Performance of semantic image retrieval is
New applications and services aim to adapt themselves to the user's context and thus require platforms that can collect, distribute, and exchange contextual information. The Context-Aware Service Platform (CASP) can help, as exemplified here in three different use cases.
different keywords or entities to form a more comprehensive view. The proposed solution aims to combine social media data and semantic linked data to extract relevant information and capture the relationship among the entities from content shared by the audience. With a targeted audience profiling, company is able to spend
Automatic indexing is the foundation and core technology of automatic documents processing. Currently most of the documents don't have Keywords, and manual indexing consumes too much time and laborious, it is also highly subjective. This paper discusses the automatic indexing method on the calculation of a statistical
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