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Automatic classification of news articles is a relevant problem due to the large amount of news generated every day, so it is crucial that these news are classified to allow for users to access to information of interest quickly and effectively. On the one hand, traditional classification systems represent documents as bag-of-words (BoW), which are oblivious to two problems of language: synonymy and...
With the rise of the three course provider including Coursera, Udacity and edX in US in 2012, massive open online courses(MOOC), as a new mode of education, boomed a wave of online higher education and swept quickly across the world. MOOC platforms, with a wide range of audience, high quality of curriculum, flexible teaching methods and rich teaching resources, are more and more popular in students...
Many researches have been carried out on network comments nowadays. In order to get more sentiment types, the paper put forward a opinion community discovery method based on sentiment of web comments and regional distribution, considering that Internet users from different regions have different perspectives on the same issue. First, the research clusters network comments into different opinion communities...
With the continuous development of the Internet technology, nowadays personalized service and recommendation technology have been paid more attentions. The paper aims at accurate user classification for tag application systems and proposes the feasible solution which can mine users' intention in reviews and extend the tag semantics by open knowledge platform. Experiments validate the proposed solution...
It is urgent to find an automatic method of an automatic orientation calculation on the large-scale text in Chinese. Rather than comment their orientation directly in comment texts, people may express their orientation on topic by describe its features using orientation words. The describe word on features indicated their orientation. The orientation of comments on object is called topic orientation...
Research of sentence orientation is aim to obtain the useful orientation information, it becomes a research focus in the nature language processing, especially in Micro-blog. Based on the existed How Net semantic similarity, this paper presents a sentence orientation identification method taking advantage of an improved algorithm for calculating Chinese term semantic orientation value. Firstly, this...
Genetic algorithms for Internet Search were classified a lot in the open literature, but one specific aspect there off - the mutational approaches - was not. This paper represents an effort to shot light on the existing mutational approaches in the context of the genetic algorithms that they are a part of. Major contributions of this paper are: (a) An original classification, which opens some potentially...
The unique characteristic of short text makes short text classification quite different from traditional long text processing. The feature space of short text is so sparse, which makes it notoriously difficult to extract sufficient and effective features. In this paper, aiming to classify the short text on web forum accurately, a novel short-text-processing method based on semantic extension is introduced...
Knowledge discovery from the Web is a cyclic process. In this paper we focus on the important part of transforming unstructured information from Web pages into structured relations. Relation extraction systems capture information from natural language text on Web pages, called Web text. However, extraction is quite costly and time consuming. Worse, many Web pages may not contain a textual representation...
Community Question Answering (CQA) has become a popular and effective mean for seeking information on the Web. It is now possible and effective to post a question asked in natural language on a popular community Question Answering (QA) portal, and to rely on other users to provide answers. These online collaborative services are attracting users and questions at an explosive rate, while how to correctly...
Feather selection is a process that extracts a number of feature subsets which are the most representative of the original meaning from original feature set. It greatly reduces the text processing time and increases the accuracy because of removing some data outliers. With the rapid development of Web 2.0 and the further evolution of the Internet, short text like micro-blog plays an important role...
Reviews on Web can help small investors make decision in selecting funds. The size of fund reviews is smaller than other products, which proposes a challenge to extract sentiment by using statistic methods. We develop a methodology to deal with this problem by using association rule to select seed words and introducing new outside resources to improve the traditional PMI performance. The result shows...
When browsing news on the web, various emotions may be evoked in readers and furthermore cause different influence on their minds and life. We expect that emotional analysis and classification of text may provide good performance and significance to users surfing the Internet. Most previous research only focus on bi-emotion classification, that is, Positive and Negative, e.g., identifying whether...
In this paper, we present an approach to automatically extract and classify opinions in texts. We propose a similarity measurement calculating semantically distances between a word and predefined subgroups of seed words. We have evaluated our algorithm on the semantic evaluation company “SemEval 2007” corpus, and we obtained the best value of Precision and F1 62% and 61%. As an improvement of 20 %...
In order to let people be able to get information from the Web easily, search engine comes into being and continues to grow and develop. People begin to explore all kinds of ranking algorithms and try to give user a good result list. However, the expression format of the web information and user queries are very simple, which results in the difficulty of determining the relevance between user queries...
Most of the previous researches on sentiment analysis concentrate on the binary distinction of positive vs. negative. This paper presents the multi-class sentiment classification problem that attempt to mine the implied rating information from reviews. We use four machine learning methods and two feature selection methods to find out whether or not the multi-class sentiment classification problem...
The system of arms information extraction based on the ontology, consists of two parts: knowledge base, processing program. It realizes the arms category determination based on text categorization, and realizes the arms object determination based on named entity recognition. It realizes the information extraction according to information extraction rules based on syntax and semantic constraint. It...
This work presents an unsupervised snippet-based sentiment classification method for Chinese unknown sentiment phrases, which is also applicable to other languages theoretically. Unlike existing Semantic Orientation (SO) methods, our proposed method does not require any Reference Word Pairs (RWPs) for predicting the sentiments of phrases. The results of preliminary experiments show that our proposed...
Content-based image retrieval (CBIR) is a difficult area of research in multimedia systems. The research has proved extremely difficult because of the inherent problems in proper automated analysis and feature extraction of the image to facilitate proper classification of various objects. An image may contain more than one objects and to segment the image in line with object features to extract meaningful...
With the growth of the Web2.0, e-commerce has become very popular in use, many websites offer the opportunity to make sales online and give the opportunity to get own an online review about objects, persons, and products. New opportunities and challenges arise as people can now actively use information technologies to seek and understand other people's opinions (sentiments) when to making their choices...
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