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In previous work, we showed that using a lattice instead of the 1-best path to represent both the query and the utterance being searched is beneficial for spoken keyword spotting. In this paper, we introduce several techniques that further improve our multi-lattice alignment approach, including edit operation modeling
KSORD (keyword search over relational database) techniques allow users to obtain information from databases, which is just like using search engines. However, the advanced techniques only realize exact queries, but not for fuzzy queries. The Rocchio algorithm of learning classification is introduced which is made a
In this paper we focus on building keyword search service over unstructured Peer-to-Peer (P2P) networks. Current state-of-the-art keyword search approaches for unstructured P2P systems are either blind or informed. Blind search methods such as flooding in Gnutella generate a large of redundant cloned messages and
We provide an overview of artificial intelligence techniques and then present a machine learning based document retrieval system we developed. GANNET (Genetic Algorithms and Neural Nets System) performed concept (keyword) optimization for user-selected documents during document retrieval using genetic algorithms. It
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...
commercial web search engines, a large fraction of returned images is not related to the query keyword. We present a SVM based active learning approach to selecting relevant images from noisy image search results. The resulting database is more diverse with more sample images, compared with other well established facial
subjectivity of deciding relevant documents empirically. Furthermore, a sentence selection strategy through extracting keywords is proposed. It calculated the word's query related feature through word co-occurrence window, and obtained the topic related feature through likelihood ratio, then combined the two features to extract
source, specifically Yahoo's ldquosuggested keywordsrdquo. These keywords are based on co-occurrence data across queries. The classifier, which is built offline with training data, makes use of the top-n results during training, but not duing testing. Thus, there is an asymmetry between the training and testing data. We
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