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Stored data in database can hide some knowledge, which is interesting, useful to hidden knowledge discover. In this context, an algorithms number a frequent itemsets and association rules extraction were presented. Special feature of these algorithms is to generation a large number of rules, making their exploitation a difficult task. In this paper we will introduce a new algorithm for association...
In community question and answering sites, pairs of questions and their high-quality answers (like best answers selected by askers) can be valuable knowledge available to others. However lots of questions receive multiple answers but askers do not label either one as the accepted or best one even when some replies answer their questions. To solve this problem, high-quality answer prediction or best...
Cyberbullying is a major problem affecting more than half of all American teens. Prior work has largely focused on detecting cyberbullying after the fact. In this paper, we investigate the prediction of cyberbullying incidents in Instagram, a popular media-based social network. The novelty of this work is building a predictor that can anticipate the occurrence of cyberbullying incidents before they...
People usually get involved in multiple social networks to enjoy new services or to fulfill their needs. Many new social networks try to attract users of other existing networks to increase the number of their users. Once a user (called source user) of a social network (called source network) joins a new social network (called target network), a new inter-network link (called anchor link) is formed...
Social media is the collection of different social networks containing different type of information. The information may be in the form of text, video, audio and image. Also various categories of users, various types of communities are available on social network. This research reports on the extraction of new keywords from messages posted on social media which will be helpful in the identification...
Nowadays, detecting health-violating restaurants is a serious problem due to the limited number of health inspectors in a city as compared to the number of restaurants. Rarely inspectors are helped by formal complains, but many complaints are reported as reviews on social media such as Yelp. In this paper we propose new predictors to detect health-violating restaurants based on restaurant sub-area...
Historically data collection in the research process involves either surveys, interviews or observation, or any combination of all three. Recent developments in the area of formative educational methods have enabled other data collection options. Data sources now available include logs from University Virtual Learning Environments (VLEs), E-learning and many other knowledge management systems. Datasets...
The day mankind met with smartphones, a new era started. Since then, daily mobile internet usage rates are increasing everyday and people have developed new habits like frequently sharing information (photo, video, location, etc.) on online social networks. Location Based Social Networks (LBSNs) are the platforms that empowers users to share place/location information with friends. As all other social...
Lexical inference problem is a significant component of some recent core AI and NLP research problems like machine reading and textual entailment. In this paper, we propose method utilizing the Probabilistic Soft Logic (PSL) model for Chinese lexical inference. The proposed PSL model not only can integrate two complementary traditional methods, i.e., the lexical-knowledge-based method and the distributional...
Mental illnesses rank as some of the most disabling conditions, affecting millions of people, across the globe. In general, the main challenge of mental disorders is that they remain difficult to detect on suffering patients. In an online environment, the challenge extends to the collection of patients data and the implementation of proper algorithms to assist in the detection of such illnesses. In...
Lately, Twitter has grown to be one of the most favored ways of disseminating information to people around the globe. However, the main challenge faced by the users is how to assess the credibility of information posted through this social network in real time. In this paper, we present a real-time content credibility assessment system named CredFinder, which is capable of measuring the trustworthiness...
User profiling from user generated content (UGC) is a common practice that supports the business models of many social media companies. Existing systems require that the UGC is fully exposed to the module that constructs the user profiles. In this paper we show that it is possible to build user profiles without ever accessing the user's original data, and without exposing the trained machine learning...
Cyberbullying is an important socio-technical challenge in Online Social Networks (OSN). With the growth trends of heterogeneous data in OSN, better network characterization, and textual feature sophistication, recent efforts have realized the value of looking at heterogeneous modes of information including textual features, social features, and image-based features for better cyberbullying detection...
Social network is a hot topic of interest for the researchers in the field of computer science in recent years. The vast amount of data generated by these social networks play a very important role in information diffusion. Social network data are generated by its users. So, user's behavior and activities are being investigated by the researchers to get a logical view of social network platform. This...
The study of Web user profiling can be traced back to 30 years ago, with the goal of extracting “semantic”-based user profile attributes from the unstructured Web. Despite slight differences, the general method is to first identify relevant pages of a specific user and then use machine learning models (e.g., CRFs) to extract the profile attributes from the page. However, with the rapid growth of the...
Information cascades exist in a wide variety of platforms on Internet. A very important real-world problem is to identify which information cascades can “go viral”. A system addressing this problem can be used in a variety of applications including public health, marketing and counter-terrorism. As a cascade can be considered as compound of the social network and the time series. However, in related...
The rapid growth of web source has changed language learning behavior. More and more people utilized web sources instead of paper books. However, the problem now is that it is overwhelming to find useful information. In addition, when considering using different words, good example sentences demonstrating nuance among words are extremely helpful but learners can hardly find them as most web dictionaries...
Drug use and abuse is a serious societal problem. The fast development and adoption of social media and smart mobile devices in recent years bring about new opportunities for advancing computer-based strategies for understanding and intervention of drug-related behaviors. However, the existing literature still lacks principled ways of building computational models for supporting effective analysis...
The development of social networks has not only improved the online experience, but also stimulated the advances in knowledge mining so as to assist people in planning their offline social events. Users can explore their favorite events, such as celebrations and symposiums, through the pictures and the posts from their friends on social networks. An effective event recommendation can offer great convenience...
Identifying extremist-associated conversations on Twitter is an open problem. Extremist groups have been leveraging Twitter (1) to spread their message and (2) to gain recruits. In this paper, we investigate the problem of determining whether a particular Twitter user engages in extremist conversation. We explore different Twitter metrics as proxies for misbehavior, including the sentiment of the...
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