The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
The process of finding out the frequency of citations for various journals or articles or research papers is known as citation analysis. The impact of any research paper can be found by computing the number of citations, the particular journal or paper received. Many researchers quote concepts or ideas from various papers and the final outcome of the paper in their discussion. But it does not always...
Sentiment classification is the main and popular task in the field of sentiment analysis. Most of the existing researches focus on how to extract the effective features, such as lexical features and syntactic features, while limited work has been done on the extraction of semantic features, which can make more contributions to sentiment classification. This paper presents a method for sentiment classification...
The traditional web service composition methods always use certain workflow to solve requests which is inflexible and needs a lot of human intervention. To solve this problem, we propose an automatic generation workflow system. This system can generate workflow automatically according to the request provided by the Web service requester. First, construct the field repository, the workflow repository...
Dynamic slicing is a practical and popular analysis technique used in various software-engineering tasks. Dynamic slicing is known to be incomplete because it analyzes only a subset of all possible executions of a program. However, it is less known that its results may inaccurately represent the dependencies that occur in those executions. Some researchers have identified this problem and developed...
Software evolves and thus developers frequently make changes to systems that are logged in version control systems. These changes are often poorly documented -- often commit logs are empty or only contain minimal information. Thus, it is often a challenge to understand why certain changes are made especially if they were introduced many months or even years ago. Understanding these changes is important...
Question Classification is a vital component of Question Answering System. In this paper we have proposed a compact and effective method for question classification. Here rather than using a two layered taxonomy of 6 course grain and 50 fine grained categories developed by Li and Roth, 2002, we have classified the questions into three broad categories. We have also studied the syntactic structure...
This paper proposes a rule based approach for sentiment analysis from Malayalam movie reviews. The research in Sentiment Analysis nowadays become one among active research areas in natural language processing. Sentiment Analysis is the cognitive process in which the user's feeling and emotions are extracted. The growing importance of sentiment analysis coincides with the growth of social media such...
Extracting key sentences with sentiments from discourses plays an important role in sentiment analysis. Different from general discourses, Internet news has its own fashion of sentiment expression. In this paper, we attempt to extract key sentiment sentences from those Internet news articles. In this paper, we propose a method, called MSF, by using multiple sources features. In our method, for each...
Automatic image annotation (AIA) for a huge number of images is one of the most difficult challenging topics for researchers in the last two decades. For labeling images accurately, more various features containing low-level image features, textual tags of images have been extracted so far; however, not whole features give useful information for each conception. Feature selection as one of the important...
The spread of social networks allows sharing opinions on different aspects of life and daily millions of messages appear on the web. This textual information can be divided in facts and opinions. Opinions reflect people's sentiments about products, personalities and events. Therefore this information is a rich source of data for opinion mining and sentiment analysis: the computational study of opinions,...
In the past years, the Web has become a huge source of opinionative data. Social media, such as Twitter, are regarded as public diaries, where millions of people express their sentiments and opinions in their daily interaction. One of the biggest challenges in the analysis of such data, is the classification of their polarity, that is, whether they carry a positive or negative connotation. For this...
The present study examined the neural markers measured in event-related potentials (ERPs) for immediate performance accuracy during a cognitive task with less conflict, i.e., a Stroop color-word matching task, in which participants were required to judge the congruency of two feature dimensions of a stimulus. In an effort to make ERP components more specific to distinct underlying neural substrates,...
As a product of Web2.0, micro-blog is developing rapidly these years. More and more information spread on the micro-blog because of its high speed and convenience, social hotspots and news events included. As a result, discovering, extraction and analyzing information become researching hotspots. By studying micro-blog text and long text cluster, this article draws a conclusion that traditional cluster...
Text documents are often high dimensional and sparse, it is a great challenge to discover the clusters among the unlabelled text data, because there are no obvious clusters by common distance measure. In this paper we present a latent subspace clustering method to find text clusters. In our algorithm, we use latent factors extracted by probability latent semantic analysis (PLSA) to generate latent...
Translation of natural language has always attracted attention of scholars world-wide, be it manual or machine based. Since, the last six decades machine translation has been witnessed. It is attempted in various Indian and Foreign languages. Machine Translation has also been attempted with different techniques. The success ratio of translation has always been an encouraging factor, which kept attracting...
Coreference resolution is the process of determining whether two expressions refer to the same entity. We adopt machine learning approach to coreference resolution. Feature selection of entity is the key of coreference resolution. This paper presents analysis methods for features which are used commonly in coreference resolution, proposes two features, entity density and antecedent characteristics...
The complex network theory is widely used in the field of keyword extraction. Through analyzing the insufficient of keyword extraction algorithms using traditional complex network, this paper proposes a new method to extract Chinese keyword based on semantically weighted network. On the basis of K-nearest neighbor coupling network, we build semantically weighted network according to the co-occurrence...
The present study proposes prediction approaches of student's grade based on their comments data. Students describe their learning attitudes, tendencies and behaviors by writing their comments freely after each lesson. The main difficulty of this research is to predict students' performance by separately using two class data in each lesson. Although students learn the same subject, there exist differences...
Due to rapid development of agent systems and robotics, more and more chances are available for humans to interact with agent-based robotic technology (e.g., Robotic vacuums, robotic surgery, etc.), this trend increases the importance of human-robot interaction including human-robot communication. For the robust human-robot communication, natural language processing (NLP) can be implemented, among...
In this paper we propose a twitter sentiment analytics that mines for opinion polarity about a given topic. Most of current semantic sentiment analytics depends on polarity lexicons. However, many key tone words are frequently bipolar. In this paper we demonstrate a technique which can accommodate the bipolarity of tone words by context sensitive tone lexicon learning mechanism where the context is...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.