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.
Automatic sentiment classification is becoming a popular and effective way to help online users or companies process and make sense of customer reviews. In this article, a learning-based method for classification of online reviews that achieves better classification accuracy is obtained by (a) combining valence shifters and opinion words into bigrams for use as features in an ordinal margin classifier...
Nowadays, many people express their opinions using user generated contains such as social media, forums and reviews. Opinion mining is a field of study that extracts sentiments from user generated contents. Because of the complexity of the Arabic language, extracting those opinions are challenging. Better representation of reviews can help to improve extraction of opinions. The traditional way of...
Keyphrases are single-word or multi-word lexemes that concisely and accurate describe the subject or side of the subject discuss in a document. Manually assigning keyphrases is tedious and time consuming, especially because of Web proliferation. Thus, automatic keyphrase generation systems are urgently needed. This study proposes a keyphrase extraction method that combines several keyphrase extraction...
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...
Relevance feedback is a powerful tool in Content based image retrieval (CBIR) systems that bridges the semantic gap and improves the performance of the system by interacting with user. In this paper, we merge the retrieval results of two short term learning (STL) algorithms using Borda count fusion method to improve the accuracy of the system. The proposed fusion method uses the advantages of individual...
Natural Language Processing (NLP) is a field which studies the interactions between computers and natural languages. NLP is used to enable computers to attain the capability of manipulating natural languages with a level of expertise equivalent to humans. There exists a wide range of applications for NLP, of which sentiment analysis(SA) plays a major role. In sentimental analysis, the emotional polarity...
The task of classifying the semantic relation between two nominals in a sentence is quite challenging due to lack of a large amount of labeled data. Existing models of semantic relation classification were built on either synthetic training data generated from unlabeled data or hand-annotated training data. Meanwhile, previous work showed that the preposition and verb in the sentences indicate important...
As multimedia data come from a wide variety of domains, each having its distinctive data distributions, cross-domain video semantic concept classification becomes an important task in semantic computing. Its challenge arises from the different distribution (in feature space) of the concept between the source and the target domain, which makes a classifier trained on a source domain perform poorly...
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...
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.