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All sorts of Malwares severely threaten users in Internet. These malwares do share some common characteristics, despite malware and its variants may vary a lot from content signatures. The common characteristics they shared can be used to reveal the real intent of malware. In this paper, we study on the behavior characteristics of malwares in Internet, and based on which we present the method to extract...
With the rapid development of the Internet, network review information shows explosive growth. How to make an accurate analysis of these web comments has become an important issue in the research of network public opinion. In this work, a traditional dictionary based algorithm is adopted to analyze text sentiment of these comments. A deep learning method is proposed to analyze the network public sentiment...
Today, web browsers are used to access and modify sensitive data and systems including intranets and critical control systems. Due to their computational capabilities and network connectivity, browsers are vulnerable to several types of attacks, even when fully patched. Browsers are also the main target of phishing attacks. Many browser attacks, including phishing, could be prevented or mitigated...
A context model plays a significant role in developing context-aware architectures and consequently on realizing context-awareness, which is important in today's dynamic computing environments. These architectures monitor and analyse their environments to enable context-aware applications to effortlessly and appropriately respond to users' computing needs. These applications make the use of computing...
Discovering topics in short texts, such as news titles and tweets, has become an important task for many content analysis applications. However, due to the lack of rich context information in short texts, the performance of conventional topic models on short texts is usually unsatisfying. In this paper, we propose a novel topic model for short text corpus using word embeddings. Continuous space word...
Quite a number of recent works have concentrated on the task of recommending to Twitter users whom they should follow, among which, the WTF (Who To Follow) service provided by Twitter. Recommenders are based either on the user's network structure, or on some notion of topical similarity with other users, or on both. We present a method for analysis of Twitter users supported by a hierarchical representation...
Semantic analysis is an important component of recommendation systems and information retrieval in computer aided detection. Previous researches have made certain breakthroughs in disease diagnosis and drugs recommended by semantic analysis. We propose a bilateral shortest paths method for computing semantic relatedness based on the human thought patterns for making sufficient use of the hyperlink...
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...
Relation discovery is a crucial task in ontology learning process. The classical approaches for relation extraction, based on statistical, syntactical or pattern matching techniques, focus typically on the taxonomic aspect. The discovery of non-taxonomic relationships is often neglected. We extend these approaches by taking into account the document structure which bears additional knowledge. This...
Internet is a very rich resource of documents that need to be analysed to extract their sentimental values. Sentiment Analysis which is a subfield of Natural Language Processing discipline focuses on this issue. The existence of sentiment lexicons in their own language is a very important resource for scientists studying in sentiment analysis field. Since many studies of sentiment analysis have been...
This work focuses on two specific types of sentimental information analysis for traditional Chinese words, i.e., valence represents the degree of pleasant and unpleasant feelings (i.e., sentiment orientation), and arousal represents the degree of excitement and calm (i.e., sentiment strength). To address it, we proposed supervised ensemble learning models to assign appropriate real valued ratings...
Question answering (QA) is the task of automatically answering a question posed in natural language. Its applied to several domains, and it is a specific type of information retrieval, that has three components such as question processing, information retrieval, and answer extraction. By analysing the user question, we intend to improve the precision of Question answering systems by focusing namely...
Provides an abstract for each of the tutorial presentations and a brief professional biography of each presenter. The complete presentations were not made available for publication as part of the conference proceedings.
Neural language models, such as word embedding, can effectively embed words into vector spaces and preserve linguistic regularities and semantic relationships. However, few researchers have shown their effectiveness on medical terms and relationships. In this paper, we study the applicability of word2vec, a well-known technique for word embedding, to embed medical terms and relations based on different...
The main problem considered in this paper is creating algorithms for estimation the relevance of documents to the search query on the basis of sentences structure analysis. To decide this problem, we use the relations between words constructed by the program system Link Grammar Parser, based on the so-called link grammar. There were suggested the natural system of links for Turkic languages, created...
Social network sites nowadays serve as important medium of communication and dissemination of information to its users. It is crucial to know users' emotion and perception towards information evolved in social network sites. The motivations for creating tools to detect emotion is increasing due to these factors. Various research conducted recently, focusing on the classification of emotion, that is...
FAQs are the lists of common questions and answers on particular topics. Today one can find them in almost all web sites on the internet and they can be a great tool to give information to the users. Questions in FAQs are usually identified by the site administrators on the basis of the questions that are asked by their users. While such questions can respond to required information about a service,...
Enormous efforts of human volunteers have made Wikipedia become a treasure of textual knowledge. Relation extraction that aims at extracting structured knowledge in the unstructured texts in Wikipedia is an appealing but quite challenging problem because it's hard for machines to understand plain texts. Existing methods are not effective enough because they understand relation types in textual level...
Synonym-based searching is considered to be a complicated problem, as text mining from unstructured data of web is challenging. Finding useful information which matches user need from the bulk of web pages is a cumbersome task. In this paper, a novel and practical synonym retrieval technique is proposed for addressing this problem. For replacement of semantics, user intent is taken into consideration...
Nodos is a new project with the main goal to promote and build a comprehensive knowledge base of performing arts, artists, cultural groups & spaces, plays and festivals. The work of recording and preservation this kind of artistic expressions contributes to the preservation of the Intangible Cultural Heritage, as has been defined by UNESCO. One of the biggest challenges related to the recording...
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