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We improve the method of relation extraction using subsequence kernel by adjusting the condition judging whether two words are equivalent and data preprocessing. The traditional subsequence methods suffer a decrease on performance of the less reliable sentence and multi-entity sentence, and their experiment only works on relatively ideal corpus, where there are exactly two entities in each sentence...
The IR-MAD components show changes in the agricultural areas as well as in the mine, and the kMAF components focus on extreme changes in the mine. Due to lack of change in the spectral signal (the change occurs in the height of the surface only) excavation of material (here brown coal) leaving the same material behind is not detected.
In this work we tackle the problem of search personalization for on-line soft goods shopping. By learning what the user likes and what the user does not like, better search rankings and therefore a better overall shopping experience can be obtained. The first contribution of the work is in terms of feature selection: given the specific nature of the domain, we combine the traditional visual and text...
Weblogs are an important source of information that requires automatic techniques to categorize them into “topic-based” content, to facilitate their future browsing and retrieval. In this paper we propose and illustrate the effectiveness of a new tf. idf measure. The proposed Conf.idf, Catf.idf measures are solely based on the mapping of terms-to-concepts-to-categories (TCONCAT) method that utilizes...
This paper describes an efficient way to presort students as possible pass / fail courses in which use of distance education as an aid or fully in its activities. The environment was used moodle and technique of data mining for classification was the SVM (Support Vector Machine). This makes it possible to efficiently classify the chance to be a student flunking a course and then act in a preventative...
Document classification is a key task for many text mining applications. However, traditional text classification requires labeled data to construct reliable and accurate classifiers. Unfortunately, labeled data are seldom available. In this work, we propose a universal text classifier, which does not require any labeled document. Our approach simulates the capability of people to classify documents...
Digital rights management systems (DRMS) are supposed to protect copyrights of the precious content for content provider. Besides access control, usage control focuses on how consumers use the digital works and prevents their content from being copied and distributed illegally. This paper introduces a technique called Windows Kernel Hook (WKH) to carry out the goal and protect the digital content...
A solution to evaluate network workload by data fusion is put forward, which can be for surveillance the traffic of interconnected communications network in order to keep the network working well by identifying potentially serious problems in the early stages and evaluating network performance. Through fusing the historic network traffic data and network online traffic data, which is based on least...
In this paper we propose a new contour based approach for people detection in Internet images. This approach relies on a large part on perceptual organization principles, at either low level edge detection and higher geometrical level. Our method is mainly compounded of two stages designed to work together: a first stage of contour detection, then a second stage of geometrical analysis. We first describe...
Extracting instances of a given target relation from a given Web page corpus seems to be the basic work to exploit nearly endless source of knowledge which provided by the World Wide Web. Supervised learning requires a large amount of labeled data, but the data labeling process can be expensive and time consuming. In this paper we present a kernel-based weakly supervised machine learning algorithm...
Since the Chinese Websites have increased in the explosive Internet era, making efficient information retrieval systems has become one of the major endeavors, especially in fields of Chinese recognition. In this paper, the authors study the integration of subsequence kernel function based on ontology. Using the vector space model (VSM) to create subsequence kernels, the kernel methodology described...
The faultload is one of the most critical components of a dependability benchmark. It should embody a repeatable, portable, representative and generally accepted fault set. Concerning software faults, the definition of that kind of faultloads is particularly difficult, as it requires a much more complex emulation method than the traditional stuck-at or bit-flip used for hardware faults. Although faultloads...
Previous research to improve the performance of Internet search engines has focused on classifying questions, sentences and user-goals but not the classification of sentences and phrases based on query intention and non-query intention. This paper investigates a classification system of query intention and non-query intention of sentences and phrases by firstly analyzing previous work and based on...
In this paper, we construct and compare several feature extraction approaches in order to find a better solution for classification of Turkish Web documents in the marketing domain. We produce our feature extraction techniques using characteristics of the Turkish language, structures of Web documents and online content in the marketing domain. We form datasets in different feature spaces and we apply...
The conventional Web browser has evolved from a viewer of static HTML pages into a platform executing fully-featured platform-independent Web applications. This transition sets an ever-increasing load to the underlying browser technology, and demand for higher performance and compatibility. In this paper, we claim that the compatibility between the browsers has improved, but the differences are still...
Categorizing Web automatically for users is a key technique of information society, and the key point of this technique is Web training and categorization. This paper researches one of the important algorithm in this field-support vector machines (SVM). By analyzing and simulating 4 kinds of kernel function and 3 ways of feature selection, polynomial kernel function and document frequency is chosen...
Ontology is applied to a real-world Web intelligent question answering system in PC troubleshooting domain as an improvement, so semantic relations need to be extracted to construct ontology semi-automatically. The paper mainly pays attention to "product-trouble" relation and "product-attribute" relation. A two stage semantic relation extraction method is proposed. In stage one,...
With the development and widely used of Internet and information technology, the Web has become one of the most important means to obtain information for people. According to the Web document classification and the theory of artificial neural network, a Web classification mining method based on classify support vector machine (SVM) is presented in this paper. The SVM network structure that used for...
Due to the huge increase in the amount of digital images available in the explosive Internet era,making efficient content based image retrieval (CBIR)systems has become one of the major endeavors. In this paper, the authors study the integration of subsequence kernel function based on ontology. Using the VSM to create subsequence kernels, The kernel methodology described here not only overcome the...
Information theorists agree that robust information are an interesting new topic in the field of programming languages, and cyberneticists concur. This is crucial to the success of our work. After years of private research into A* search, we disconfirm the practical unification of lambda calculus and Moore's Law, which embodies the appropriate principles of cryptography. Our focus here is not on whether...
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