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The search engine, keyword extraction is an important technique. In this paper, aiming at the defects of the traditional keyword extraction algorithm, we proposed an improved weight computation strategy. The experimental results show that, the improved method's results are significantly better results than the
ordinary users to use. In this paper, we propose a novel keyword-based user interface system EasyUI for achieving web-scale data integration and easy to use for ordinary users. Dealing with heterogeneity on the web-scale presents many new challenges. We proposed new methods to address these challenges, i.e., indexing schemata
In this paper, reclassification for the current classification through K-means would be implemented based on the feedback of Web usage mining in order to improve the accuracy of news recommendation and convergence of classification. It could extract most relative keywords and eliminate the disturbance of multi-vocal
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...
which we cannot extract emotions by traditional sentiment analysis techniques. Some sentences in the textual reviews may derive deep emotions but do not contain any keyword to detect those emotions, so we used audiovisual reviews in order to detect emotions from the facial expressions of the customer. In this paper we take
Manual tagging has an important impact to performance of image/video searching by keyword. However, users usually mark tags only landmarks are as on only a few images in library and leave most contents untagged. If landmarks from different places are look alike, it is hard to distinguish even though surroundings are
temporal changes of brand-related keyword networks. Our analysis enables trends in brand awareness to be systematically traced and evaluated. This allows various other analyses, such as advantages and disadvantages of the brand, and a comparison with its competitors.
this module and early results of CBIR enabled the combination of content-based retrieval and keyword retrieval. It made some improvements to the retrieval performance and narrowed the gap of semantics. Experimental results demonstrated that this project can to a certain extent help users more precisely retrieve to their
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
metrics used in text categorization by using local and global policies. For the experiments, we use three datasets which vary in size, complexity and skewness. We use SVM as the classifier and tf-idf weighting for term weighting. We observed that almost in all metrics, local policy outperforms when the number of keywords is
The gain of somatosensory afferent paths from the lower limb to the cerebral cortex was investigated during the acquisition of one target location during plantar flexion. Sensory gain was measured as the magnitude of somatosensory evoked potentials (SEPs) following electrical stimulation of a peripheral nerve in the lower limb, and was recorded from the scalp. We hypothesized gain attenuation of SEPs...
In this paper, we propose the ldquoaddedrdquo use of proximity search to a Web search query for narrowing down the set of documents returned as answers to a keyword based search query. This approach adds value to Web search query results by allowing users to better express what they are looking for. Most of the
The study aimed at analyzing the keywords of the Macau Special Administrative Region's 2012 and 2013 annual policy addresses. The contribution of the study included the following two points. First, the study used the text mining method in order to explore the content of policy address. Second., the study applied the
filter contains one standard Bloom filter and multiple Counting Bloom filters, and the design of multi-level structure can accurately represent weights of interest keywords. According to this structure, the interest adjustment algorithm and the keywords matching algorithm are proposed at the same time. After experimental
existing short cognitive screening tests at their optimal cut‐off scores.
Methods
A search of the electronic journal databases EBSCO, Psych info, and Science Direct was undertaken using the keywords “Quick Mild Cognitive Impairment Screen,” “QMCI,” “accuracy,” “sensitivity,” and “specificity
Although much research on Music Information Retrieval (MIR) has been done in the last decade, the input of the current MIR to specify a user query for finding a similar piece of music is still either by the existing old-fashioned keywords or by music contents. We aim to realize a new type of MIR equipped with brain
to describe a document instead of traditional keywords vector, which is based on merging words with high similarity and using a concept to describe the semantic feature rather than a series of words. It not only reduces feature dimension but also adds semantic information to the vector. We also use sentence (document
the word attributes are trained by the labeled training weblogs, and some keywords of a testing weblog are extracted as one part of the tags based on the probability distributions. Then the other part of the tags are obtained from the first part ones with the help of Latent Semantic Indexing (LSI) model. Experiments on a
Traditional automatic classifiers often conduct misclassifications. Folksonomy, a new manual classification scheme based on tagging efforts of users with freely chosen keywords can effective resolve this problem. Even though the scalability of folksonomy is much higher than the other manual classification schemes, the
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.