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Spatial keyword querying has attracted considerable research efforts in the past few years. A prototypical query takes a location and keywords as arguments and returns the k objects that score the highest according to a ranking function. While different scoring functions have been used, how to compare different
proposed approach uses a segmental DTW, wherein search is carried out only at syllable boundaries. This reduces the search complexity by 9 times compared to conventional sliding window DTW. The first pass of the proposed method uses a minimum set of templates for a keyword to search through the segmented audio. New templates
This paper proposes a Research paper Similarity system that measures the similarity of an input paper with other papers based on the summarized version of each paper. Currently, This system will take into account 2 different types of summarization for papers based on the different types of keywords,i.e, Normal
In the age of Internet, with the online information explosive growth, people want to find information we need in the cyberworld fleetly and exactly. The information retrieval method based on the keyword or the simple logic-combination of the keywords has been unable to meet the people's need of information getting to
Recently, the multi-label learning has drawn considerable attention as it has many applications in text classification, image annotation and query/keyword suggestions etc. In recent years, a number of remedies have been proposed to address this challenging task. However, they are either tree based methods which has
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
retrieve the routes that are the most textually relevant to the user-specified query keywords subject to a travel cost constraint. BCIR query is particularly helpful for tourists and city explorers to plan their travel routes. We will show that BCIR query is an NP-hard problem. To answer BCIR query efficiently, we propose an
Information Retrieval (IR) methods are commonly based on words, these methods allow the user to formulate a query through keywords. However, there are situations where the user has only one example document and based on this example it is needed to recover the most similar documents in a collection. This paper
Based on the research and analysis of interactive text properties, the word frequency statistics and synonyms merger are imported to obtain the keywords of interactive text. The Sentence similarity is used to describe the degree of coupling between sentences. Then a novel topic partition algorithm based on average
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