Serwis Infona wykorzystuje pliki cookies (ciasteczka). Są to wartości tekstowe, zapamiętywane przez przeglądarkę na urządzeniu użytkownika. Nasz serwis ma dostęp do tych wartości oraz wykorzystuje je do zapamiętania danych dotyczących użytkownika, takich jak np. ustawienia (typu widok ekranu, wybór języka interfejsu), zapamiętanie zalogowania. Korzystanie z serwisu Infona oznacza zgodę na zapis informacji i ich wykorzystanie dla celów korzytania z serwisu. Więcej informacji można znaleźć w Polityce prywatności oraz Regulaminie serwisu. Zamknięcie tego okienka potwierdza zapoznanie się z informacją o plikach cookies, akceptację polityki prywatności i regulaminu oraz sposobu wykorzystywania plików cookies w serwisie. Możesz zmienić ustawienia obsługi cookies w swojej przeglądarce.
Some online social networks (OSNs) allow users to define friendship-groups as reusable shortcuts for sharing information with multiple contacts. Posting exclusively to a friendship-group gives some privacy control, while supporting communication with (and within) this group. However, recipients of such posts may want to reuse content for their own social advantage, and can bypass existing controls...
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...
In online social networks, people may want to make new friends to maximize their social influences. For example, business page owners on Facebook want to influence as many people as possible for commercial advantages. Hence, we study a friend recommendation strategy with the perspective of social influence maximization. For the system provider (e.g., Facebook), the objective is to recommend a fixed...
This paper presents a methodology allowing the execution of Bounded Model Checking (via CBMC) and Abstract Interpretation (via Frama-C) analyses on large, real case, C codebases. Then the paper shows some of the results that can nowadays be achieved with relatively new tools like Clang Static Analyzer and Facebook Infer. Finally, a brief introduction on SonarQube and how it can be used to display...
People are suffering from a range of risks in the ubiquitous networks of current world, such as rumours spreading in social networks, computer viruses propagating throughout the Internet and unexpected failures happened in Smart grids. We usually monitor only a few users of detecting various risks due to the resource constraints and privacy protection. This leads to a critical problem to detect compromised...
Spatial keyword querying has attracted considerable research efforts in the past few years. A prototypical query takes a location and keywords as arguments and returns the k objects that score the highest according to a ranking function. While different scoring functions have been used, how to compare different ranking functions for spatial keyword querying still remains an open question with little...
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...
This paper introduces a vocabulary learning application called “Avocado” that aims to provide suitable learning materials to learners by modeling their language proficiency and topical interests. A learner's vocabulary level is estimated through aggregating words that he identifies as difficult in given text passages; and his topical interests are gathered by utilizing the social network (Facebook)...
Conventional automatic document classification methods are currently faced with challenges in terms of learning time and computing power, owing to the ever-increasing amount of data on the web. In this paper, we propose an efficient classification method that uses time series-based dataset selection. In the proposed method, the dataset is split based on time series data and the best set of testing...
The emergence of social networks and the communication facilities they offer have generated an enormous informational mass. This social content is used in several research and industrial works and has had a great impact in different processes. In this paper, we present an overview of social information use in Information Retrieval (IR) and Recommendation systems. We first describe several user profile...
Nowadays, social networks have been used widely. They help people communicate with family, friends or colleagues easily. However, they are lack of effective protection and monitoring about message transmission. In addition, the rapid updates of messages and user information also give difficulties to administrators. The existing security protection mechanisms in social networks could not protect users'...
Automatic personality recognition aims to assign a personal profile to the author by measuring the Big Five personality factors automatically. The present paper focuses on an approach developed to recognize the personality of the author by evaluating their writings. The score for each of the Big-Five personality traits is computed programmatically. Based on the essays of the author as an input, parse...
Framing is a phenomenon that is studied and debated widely in sociology and political science. It refers to the manner in which audiences interpret information and justify their claims or activities. The subconscious influence of framing might lead to opinion changes and social movements. However, multi-frame classification on microblogging data has not yet been investigated. In this study, we aim...
The infinite relational model (IRM) is a Bayesian nonparametric stochastic block model; a generative model for random networks parameterized for uni-partite undirected networks by a partition of the node set and symmetric matrix of inter-partion link probabilities. The prior for the node clusters is the Chinese restaurant process, and the link probabilities are, in the most simple setting, modeled...
Cyberbullying is the most common online risk for adolescents, and it has been reported that over half of young people do not tell their parents when it occurs. Cyberbullying involves the deliberate use of online digital media to communicate false or embarrassing information about another person. While previous work has extensively analyzed the nature and prevalence of cyberbullying, there has been...
Cyberbullying is the deliberate use of online digital media to communicate false, embarrassing, or hostile information about another person. It is the most common online risk for adolescents and well over half of young people do not tell their parents when it occurs. While there have been many studies about the nature and prevalence of cyberbullying, there has been relatively less work in the area...
We focus on the vertex-centric (VC) model introduced in Pregel, a Google system for distributed graph processing. In particular, we consider two popular implementations of the VC model: Apache Giraph and GraphChi. The first is a VC system for cluster computing, while the second is a VC system for a single PC. Apache Giraph became very popular after careful engineering by Facebook researchers in 2012...
Although the spiral of silence theory has been studied thoroughly in the traditional dissemination field, to our best knowledge, no one has clearly verified the applicability of the spiral of silence theory in social networks based on the real information propagation datasets. In this paper, we focus on the disparity between majority and minority opinions, we verify the applicability of the spiral...
This article researches on node importance ranking of multiplex network. Existing node importance ranking methods are amost monoplex network using only single relationship. However, in real life a person often has various relationships, so how to rank nodes of multiplex network is more realistic and meaningful. In this article, we propose a multiplex network node ranking method based on weighted aggregation...
Sampling-based approximate query processing (AQP) method provides a fast way, in which the users can obtain a trade-off between accuracy and time consumption by executing the analytical application on a sample of data rather than the whole dataset. AQP method is usually adopted to support Big Data analysis efficiently, and there are two major AQP methods: (1) central limit theorem (CLT) based online...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.