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We are developing an individual e-learning system using two communication cameras and a pen capture tool on whiteboard for university students. In this research, keywords recognition for the written characters by the lecturer on the whiteboard is important for indexing the scene database. We are considering the
Online underground economy is an important channel that connects the merchants of illegal products and their buyers, which is also constantly monitored by legal authorities. As one common way for evasion, the merchants and buyers together create a vocabulary of jargons (called "black keywords" in this
Text keywords at different semantic levels have different semantic representation abilities. Although words have been organized by semantic dictionaries (e.g. WordNet) with exact semantics, the dictionaries can not be constructed automatically by machine and there are still many words which are not included in the
information are provided to user if user demands for it. Search queries are the most important part in searching data on internet. A search query consists of one or more than one keywords. A search query is searched from the database for exact match, and the traditional searchable schemes do not tolerate minor typos and format
This paper proposes a structure that automatically analyzes the parameters of Chinese test items. This structure utilizes latent semantic analysis (LSA) to analyze the relationships of keywords among all test items in an item bank. It also uses the similarity measure to calculate the similarity degree of keywords. We
-processing of Web search results have been extensively studied to help user effectively obtain useful information. This paper has basically three parts. First part is the review study on how the keyword is expanded through truncation or wildcards (which is a little known feature but one of the most powerful one) by using
paper, we propose simulating an automated system (SAS) which consists of a source dictionary, a destination dictionary, and a keyword comparison method. Our preliminary work uses MEDLINE and MEDICINENET as two vocabularies and simple comparison and Levenstein Distance as two keyword comparison methods.
) based DNS query traffic from the Internet through January 17th to February 1st, 2009. (2) We found the large NS RR based DNS query traffic including only a keyword "." in the total DNS query traffic from the Internet. (3) We also found that the unique source IP address based PTR DNS traffic entropy slightly increased
Question Understanding of Chinese Question-Answering System generally includes steps such as: word segmentation, POS Tagging, keywords expansion, information retrieval etc. The extended keyword set usually has redundant messages and part of the words and phrases may be not relevant to the question. Consequently
improve the performance of English-Hindi CLIR system using English and Hindi WordNet, Local Expansion using initial query, definition based pre query expansion and keyword ranking. The pre and post query expansion helps to improving the performance of English-Hindi CLIR system and based upon past experiences the proposed
combine folksonomy, keyword and facet-based retrieval methods to retrieve software requirements related to users' interests. We add semantic ontology and users' feedback to obtain better software requirements that satisfy users' preferences to enhance software requirements retrieval performance. Finally, we demonstrate the
Automatic image annotation is crucial for keyword-based image retrieval. There is a trend focusing on utilization of machine learning techniques, which learn statistical models from annotated images and apply them to generate annotations for unseen images. In this paper we propose MAGMA - new image auto-annotation
analysis and results ranking. For semantic annotation, we use domain ontology and two bilingual dictionaries to extract keywords for annotation. For query analysis, we present a method which combines lexical relationship and semantic relationship to analyse user's query. And for results ranking, we propose a modulative method
neighbor search of videos from Internet. The fundamental problem lies on the scalability of a search technique, in face of the intractable volume of videos which keep rolling on the Web. In this paper, we investigate scalability of several well-known features including color signature and visual keywords for Web-based
relational database of web pages. So there are many researches focusing on the search in these relational database with keywords, compared with these researches, our algorithms are mainly based on bags using the greedy algorithms and supporting the phrase recognition by utilizing multiple dictionaries. We make a comparison
detail. The paper presents the similarity algorithm of domain keywords and common words respectively and integrates them into the question similarity. Experimental results show that the proposed method can achieve good performance and the system is applied.
To support understanding of news, we propose a novel TEC model (Topic-Event Causal relation model) and describe the method to construct a Causal Network in the TEC model. The model includes two types of keywords to represent casual relations: topic keywords, which describe topics, and event keywords, which describe
This paper presents an integrated approach to automatically provide an overview of content on Thai websites based on tag cloud. This approach is intended to address the information overload issue by presenting the overview to users in order that they could assess whether the information meets their needs. The approach has incorporated Web content extraction, Thai word segmentation, and information...
We introduce a new method for discovering latent topics in sets of objects, such as documents. Our method, which we call PARIS (for Principal Atoms Recognition In Sets), aims to detect principal sets of elements, representing latent topics in the data, that tend to appear frequently together. These latent topics, which we refer to as `atoms', are used as the basis for clustering, classification, collaborative...
With the rapid development of World Wide Web, the Web malicious attackers have taken the initiative jamming in Chinese to transform the form of the key words to be avoided being mined by the software existed. So how to filter the unhealthy Web page quickly and effectively has become the main content of the Web security. Because of the limitation of traditional rigid strings matching on the key words...
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