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Generally, some object-based features are more relevant to a thematic class than other features. These strongly relevant features, termed as class-specific features, would significantly contribute to thematic information extraction for very high resolution (VHR) images. However, many existing feature selection methods have been designed to select a good feature subset for all classes, rather than...
This paper surveys Audio Information Retrieval (AIR) using a literature review and classification of articles from 1994 to 2010 with a keyword index and article abstract in order to explore how AIR methodologies and applications have developed during this period. Based on the scope of many papers and journals of AIR, this paper surveys and classifies AIR problem domains into five domains: AIR framework,...
Since the traditional classification algorithm does not work well in the case of short-text classification, we propose a search-based method employing Na'iveBayes classification algorithm. This paper describes the whole process, including the classification algorithms, training and the evaluation. The results indicate that the classifier has better performance comparing with other methods.
The Multimedia Information Retrieval (MIR) in the P2P networks has been widely studied. In this paper, we propose a new comprehensive similarity function to calculate the similarity of peers in the P2P networks so as to classify these peers. We also apply the relevance feedback in the process of retrieval in order to improve the speed and accuracy of retrieval. In simulation, we compare our algorithm...
In the blogosphere, the amount of digital content is expanding and for search engines, new challenges have been imposed. Due to the changing information need, automatic methods are needed to support blog search users to filter information by different facets. In our work, we aim to support blog search with genre and facet information. Since we focus on the news genre, our approach is to classify blogs...
In Web database integration, crawling data pages is important for data extraction. The fact that data are contained by multiple result pages increases the difficulty of accessing data for integration. Thus, it is necessary to accurately and automatically crawl query result pages from Web database. To address this problem, we propose a novel approach based on URL classification to effectively identify...
Non-wood forest is a kind of important forest resource. This paper focused on the information extraction of non-wood forest based on Advanced Land Observation Satellite (ALOS) data. Band characteristics were analyzed to get understanding of this data wholly by information content, correlation coefficient and Optimum Index Factor (OIF). A new set of data with eight bands were obtained by the fusion...
The optimal exploitation of the information provided by hyperspectral images requires the development of advanced image processing tools. This paper introduces a new hierarchical structure representation for such images using binary partition trees (BPT). Based on region merging techniques using statistical measures, this region-based representation reduces the number of elementary primitives and...
This paper presents the building of part-of-speech Tagger for Malayalam Language using Support Vector Machine (SVM). POS tagger plays an important role in Natural language applications like speech recognition, natural language parsing, information retrieval and information extraction. This supervised machine learning POS tagging approach requires a large amount of annotated training corpus to tag...
This work proposes a hybrid model for text document classification for information retrieval using Naive Bayes and Rough set theory. Rough set theory is used for feature reduction and Naive Bayes theorem is used for classification of documents into the predefined categories by means of the probabilistic values. The deployment of the proposed model is planned through an enhanced method of the utilization...
Hierarchical taxonomies are used to organize and retrieve information in many domains, especially those dealing with large and rapidly growing amounts of information. In many of these domains data also tends to be multi-label in nature. In this paper, we consider the problem of automated text classification in these scenarios. We present a post-processing based approach that performs smoothing on...
Document classification is one of the prominent area of research evolved as a result of exponential growth in the usage of electronic documents. Classification of documents demands for understanding of document units by removing insignificant data and improving computational efficiency. This paper deals with the approaches aimed at dimensionality reduction (DR) in document units for Telugu. Bag of...
Tempo is a common criterion by which humans describe and categorize music, and this has spawned a large amount of research in the field of automatic tempo estimation. Most tempo estimation systems focus mainly on detecting the temporal repetition and periodicity present within a signal, and represent tempo as a count of beats-per-minute (BPM). However, in real-world music retrieval applications such...
Question classification plays a crucial important role in the question answering system. Recent research on question classification for open-domain mostly concentrates on using machine learning methods to resolve the special kind of text classification. This paper presents our research about Chinese question classification using machine learning method and gives our approach based on SVM and semantic...
A robust and efficient technique for automatic music mood annotation is presented. A song's mood is expressed by a supervised machine learning approach based on musical features extracted from the raw audio signal. A ground truth, used for training, is created using both social network information systems and individual experts. Tests of 7 different classification configurations have been performed,...
We consider the problem of content extraction from online news Web pages. To explore to what extent the syntactic markup and the visual structure of a Web page facilitate the extraction of its content, we compare two state-of-the-art classifiers as first instantiations of a general framework that allows for proper model comparison. To this end, we introduce the publicly available NEWS600 corpus, a...
Despite the growth of the Web in recent years, some portion of the Web remains largely underdeveloped, as shown in lack of high quality contents. An example is the botany specific Web directory, in which lack of well-structured Web directories have limited user's ability to brows the necessary information. In this research we propose an improved framework for constructing a specific Web directory...
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 word in one category based on feedback of Web usage. The reclassification of news...
There are various opinions on the Web, and analyzing them is an important task. Although many previous studies focused on analyzing subjective evaluative expressions, objective evaluative expressions which describe positive or negative facts are also informative information. In this paper, we study extraction and classification of subjective and objective evaluative expressions on Japanese Web documents...
Indexing, retrieval, and summarization in recordings of meetings have, to date, focused largely on the propositional content of what participants say. Although objectively relevant, such content may not be the sole or even the main aim of potential system users. Instead, users may be interested in information bearing on conversation flow. We explore the automatic detection of one example of such information,...
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