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reports, etc. The system provides keyword-based and semantic-driven data matching methodology to extract the specific information from the textual clinical documents. The matching methodology provides the capabilities to recognize the selected keywords and the related semantics in the documents. Through the extraction
This paper presents a text query-based method for keyword spotting from online Chinese handwritten documents. The similarity between a text word and handwriting is obtained by combining the character similiarity scores given by a character classifier. To overcome the ambiguity of character segmentation, multiple
This demo illustrates an XML search engine TargetSearch that addresses an open problem in XML keyword search: given relevant matches to keywords, how to compose query results properly so that they can be effectively ranked and easily digested by users. The approaches adopted in the literature generate either
Keyword spotting becomes a very important branch of speech recognition. But the acoustic mismatch between training and testing environments often causes a severe degradation in the recognition performance. This paper presents an improved keyword spotting strategy. A fuzzy search algorithm is proposed to extract
Multiple keyword matching is an important problem in text processing that involves the location of all the positions of an input string where one or more keywords from a finite set occur. Modern multiple keyword matching algorithms can scan the input string in a single pass by preprocessing the keyword set, an
Audio mining is a speaker independent speech processing technique and is related to data mining. Keyword spotting plays an important role in audio mining. Keyword spotting is retrieval of all instances of a given keyword in spoken utterances. It is well suited to data mining tasks that process large amount of speech
Based on the analysis of the insufficiencies of the present Chinese matching algorithms, by examining the characteristics of approximately duplicate records, this paper proposes a method of duplicate record cleaning based on a reformative keywords matching algorithm. Experiments show that this method improves Recall
Unmanned Aerial Vehicles (UAVs) are increasingly popular. As a result of the tremendous number of UAVs, especially recreational UAVs, regulation becomes a challenge we are confronted with. Protocol reverse engineering offers a way to understand and regulate the drones effectively. Extracting keywords is an
Efficient discovery of information based on partially specified and misspelled query keywords is a challenging problem in large scale peer-to-peer (P2P) networks. This paper presents QPM, a P2P search mechanism for efficient information retrieval with misspelled and partial keywords. QPM uses the double metaphone
classic statistical method for sentence alignment, we propose an improved approach to align the initial bilingual resources, in which two factors, bilingual keyword pairs and matching patterns are introduced. Experimental results show that our sentence aligner supported by the new approach achieves performance enhancement by
When match against Chinese keyword for network content audit, one of the biggest problems is that there is interference of ??noise characters??, it makes the traditional way using explicit string pattern to match infeasible. Regular expression matching can solve the problem perfectly, but the DFA-base approaches for
enhanced. Three PDA integrated outdoor observation activities and worksheets were arranged for elementary school's ecology learning. A scoring rubric and two scoring methods, i.e. keyword pattern-matching (PM) and Latent Semantic Analysis (LSA), have been developed for rating the construct responses of worksheet. The scoring
String matching is a fundamental issue in computer science. This paper presents a lightweight string matching algorithm for short pattern matching, in which less than 20 keywords are often involved in the pattern set. The new algorithm makes use of condensed hash tables and computes the shift distance after each test
This paper proposes a system of retrieving English sentences by utilizing linguistically structural information. The userpsilas query consists of a sequence of keywords. The system automatically identifies dependency relations between occurrences of the keywords in sentences and classifies the sentences according to
The paper considers increasing the precision of detection of words in unsupervised keyword spotting method. The method is based on examining signal similarity of two analyzed media description: registered voice and a word (textual query) synthesized by using Text-to-Speech tools. The descriptions of media were given
, the system carry out conversation with the user to explicitly understand his/her needs and accordingly filters search results for display. The conversation between the system and the user is based on word co-occurrence keyword extraction and Artificial Intelligence Markup Language (AIML) technique. As per initial
With the number of registered Web services growing, Identifying desired Web service is crucial for Web users. Current keyword based service search are inefficient in two main aspects: poor scalability and lack of semantics. Firstly ,the users are overwhelmed by the huge number of irrelevant services returned. Secondly
The proliferation of Web services demands for a discovery mechanism to find advertisements that satisfy the requests more accurately. OWL-S provides a capability-based description and logic inference mechanism for semantically matching. UDDI provides a registry of businesses and Web services, but its keyword search
XML employs a tree-structured model for representing data, and queries over XML documents are typically represented as twig patterns. At the same time, keyword search over XML documents has been well studied because of its intuitive and friendly query interface. Consequently, XQuery Full-Text emerges as a full-text
answers, such as short-answer questions, discussion questions etc. There are two factors that will affect the subjective item scoring: knowledge point and the nearness level. The unidirectional nearness algorithm in the fuzzy mathematics only focus on the keyword matching, but ignore the scoring of the knowledge point and
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