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Online services such as Facebook or Twitter have public APIs to enable an easy integration of these services with third party applications. However, the developers who design these applications have no information about the consistency provided by these services, which exacerbates the complexity of reasoning about the semantics of the applications they are developing. In this paper, we show that is...
Recommender systems help users to find their favorite products based on their historical preferences. They are commonly utilized in a variety of areas such as movies, music, research articles, search queries and social tags. They exploit the power of social knowledge bases to detect semantic similarities among items and users. In this paper, a personalized meta-level hybrid recommendation technique...
Online social networks (OSNs) are platforms which facilitate social interactions between their users through message exchange, photo and video sharing, status updates, etc. One of the most popular OSNs is Facebook. Connections between users on Facebook are modeled through concept of friendship. Each connection between users is binary — two users either are or aren't "friends". Information...
In recent years, emotions expressed in social media messages have become a vivid research topic due to their influence on the spread of misinformation and online radicalization over online social networks. Thus, it is important to correctly identify emotions in order to make inferences from social media messages. In this paper, we report on the performance of three publicly available word-emotion...
Social networks have become one of the most important research platforms in the big data era. Modelling social networks enables researchers and engineers to understand and analyze their intrinsic properties thereby implementing their real applications. A number of studies on social network modelling focus on a few characteristics, such as the number of edges (i.e., two-star motifs), scale-free degree...
The analysis of node influence plays important role in product marketing, public opinion analysis, disease transmission and other fields. Researchers have proposed a variety of methods to measure node influence, with the rapid expansion of the scale of social networks, Degree Centrality algorithm attracts much attention for its lowest time complexity, however, its result is not sufficiently accurate...
Online social networks (OSN) are one of the most widely adapted services of the Internet infrastructure, Facebook being one of the most popular among them. Facebook models connections between its users through the concept of “friendship”. However, the type and intensity of these connections between different people on Facebook vary significantly. In most cases, friends on Facebook correspond to mere...
In social media, after many candidate posts are chosen by satisfying functional criteria of target posts, users require a selection algorithm to further rank the candidate posts with their nonfunctional criteria. Therefore, this study proposes a novel algorithm, named BD-FGRA (Big Data-Fuzzy Grey Relational Analysis), to handle posts on parallel over the Spark platform by selecting the top-N posts...
Hex is going to be more and more popular because of its simple rules. The simple rules also bring enormous situation of Hex. It is hard for computer to assume the best situation after several rounds even simply use Alpha-beta pruning in a few minutes. In this page, we analysis the Hex and compare MTD(f) with using Alpha-beta pruning only. Our conclusion is that MTD(f) can make it much more effective...
Knowledge acquisition is an iterative process. Most prior work used syntactic bootstrapping approaches, while semantic bootstrapping was proposed recently. Unlike syntactic bootstrapping, semantic bootstrapping bootstraps directly on knowledge rather than on syntactic patterns, that is, it uses existing knowledge to understand the text and acquire more knowledge. It has been shown that semantic bootstrapping...
SkillsRec recommender (Skills based Recommender) is a novel Latent Semantic Analysis model driven recommendation system for online Personal Learning Environments that develops skill-similarity based user-user recommendations through semantically analyzing teacher-competencies and learner-interests. The recommender provides a solution to the inherent, massive and exponentially increasing information-overload...
In this paper, we present a graph partitioning algorithm to partition graphs with trillions of edges. To achieve such scale, our solution leverages the vertex-centric Pregel abstraction provided by Giraph, a system for large-scale graph analytics. We designed our algorithm to compute partitions with high locality and fair balance, and focused on the characteristics necessary to reach wide adoption...
Social interactions can be inferred on the web using the mailing list and home page links. It also represents the social lives of the individuals, collaborations, communities and relationship. Social networking groups are becoming increasingly important due to the volume and activities. Thus, the structure of the network, connectivity, movement of members from one group to another and change of interest...
Social influence analysis has become one of the most important technologies in modern information and service industries. It will definitely become an essential mechanism to perform complex analysis in social networking big data. It is attracting an increasing amount of research ranging from popular topics extraction to social influence analysis, including analysis and processing of big data, social...
From the day internet came into existence, the era of social networking sprouted. In the beginning, no one may have thought internet would be a host of numerous amazing services like the social networking. Today we can say that online applications and social networking websites have become a non separable part of one's life. Many people from diverse age groups spend hours daily on such websites. Despite...
Currently Internet usage has increased a lot due to bandwidth availaility and technology advancements. Internet is widely used for knowledge sharing, online review of products etc. Many open forums, blogs are used for this purpose. Since many users are contributing their opinions towards any query submitted by information seeker, there is a possibility of confusion. Often opinions contradict with...
The diameter of a graph is the maximum distance among all pairs of nodes. Determining the diameter of a graph in the tradition way costs O(mn) time, where n is the number of nodes and m is the number of edges. A social network can be modelled as a graph. With the rapid expansion of social networks, the number of nodes in a social network could be hundreds of millions. In this paper, we propose a new...
The paper proposes a framework to find time-dependent social network influential users as well as measure their sentiment degree. Klout is the app that could calculate social network users' influence scores that could be used as references for businesses to know who have influence power. However, Klout could not tell who the influential users are in a specific time period and Klout could not tell...
This paper present a new recommendation algorithm based on contextual analysis and new measurements. Social Network is one of the most popular Web 2.0 applications and related services, like Facebook, have evolved into a practical means for sharing opinions. Consequently, Social Network web sites have since become rich data sources for opinion mining. This paper proposes to introduce external resource...
The explosion of Social Network Analysis (SNA) in many different areas and the growing need for powerful data analysis has emphasized the importance of in-memory big data processing in computer systems. Particularly, large-scale graphs are gaining much more attention due to their wide range of application. This rise, accompanied by a massive number of vertices and edges, led computations to become...
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