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.
The interests of individual Internet users fall into a hierarchical structure which is useful in regards to building personalized searches and recommendations. Most studies on this subject construct the interest hierarchy of a single person from the document perspective. In this study, we constructed the user interest hierarchy via user profiles. We organized 433,397 user interests, referred to here...
Nowadays, life unfolds in a digitised world, in which, each person can have access to a huge amount of information through the use of Internet. In this situation, most of daily activities are being influenced by a new kind of society that allows ubiquitous and instantaneous interaction among its members. The creation of social platforms (SPs) has strengthened human relationships at such point that...
Based on the existing research of Chinese text clustering, this paper proposes an improved algorithm for the optimization of short term semantic clustering based on social media. The method of weighted factor is introduced to optimize text distance formula and related mathematical proof, the calculation process optimization design from text, written text distance calculation algorithm, the simulation...
This paper provides insight into the effects of cross-border infrastructure and logical interconnections in Africa on both intra-country and cross-border latency on end-to-end Internet paths, by comparing Internet performance measurements between different countries. We collected ICMP pings between countries using Speedchecker and applied a community detection algorithm to group countries based on...
Network traffic classification technique is currently a key part of network security systems. In recent years, some network traffic classification algorithms using machine learning based on packet and flow level features have been proposed, yet the results are frequently disappointing. On the one hand, obtaining a large, representative, training data set that is fully labeled to train a classifier...
Due to the emerging Big Data paradigm, traditional data management techniques result inadequate in many real life scenarios. In particular, the availability of huge amounts of data pertaining to social interactions among users calls for advanced analysis strategies. Furthermore, heterogeneity and high speed of this data require suitable data storage and management tools to be designed from scratch...
In order to improve booking tickets experience of the users of Railway Online Ticketing System and ensure the system normally running, Railway Online Ticketing System's users abnormality booking the tickets detection model based on the traditional K-Means and FP-Growth algorithm is proposed. Firstly, preliminary filter user features by the Random Forest Algorithm based on Spark MLlib to identify the...
Synonyms extraction is a fundamental research, which is helpful to text mining and information retrieval. In this paper, we propose method to extract synonymy from text, the method employs spectral clustering and word2vec. First, the word2vec model is trained by a large-scale English Wikipedia corpus. Then, we extract keywords from a text and use the trained model to generate similarities among these...
With the rapid development of the Internet, social networking platforms and mobile technologies, people are increasingly in contact with the Internet and share their views with others on the Internet. The content that people care about and talk about every day is a hot topic, hot topics can play an important role in politics, economy, culture and other fields, so the research on hot topics has a great...
Since Web 2.0 be announced, social media services become popular in these years. Due to multiple relationships existing simultaneously among the members of the community in real world, to detect all overlapping communities from complex networks is becoming an important issue. The paper proposed a novel overlapping community detection method by seed set expansion with local cluster coefficient (LCC)...
With the development of the Internet, it is vital for the security of the Internet to detect web-based anomalies. Clustering based on feature extraction by manually has been verified as a significant way to detect new anomalies. But the presentations of these features can't express semantic information of the URLs. In addition, few studies try to cluster the anomalies into specific types like SQL-injection...
With the development of Internet technology and the arrival of the era of big data, it is necessary to analyze and excavate the micro video data. It can help micro video creators to create better to analysis micro video data. This paper mainly introduces the structure design, key technical points and specific implementation steps of the micro video topic recommendation system.
Internet access has become a requirement to participate in society; however, the majority of the world's population is not yet online. Citizens can self-organize cooperatively to crowdsource community network infrastructures and achieve Internet access. In order to help address that challenge, this paper provides an analysis of a crowdsourced Internet access mechanism: the distributed Web proxy service...
With tags widely used in organizing and searching contents in massive data era, how to automatically generate appropriate tags of resource for users became a hot issue on social networks research. Tag recommendation for text resource can be modeled as a keyword extraction problem, hence topic modeling such as LDA which extracts latent semantic topics from text is suitable for tag recommendation. However,...
Internet videos provide a virtually boundless source of audio with a conspicuous lack of localized annotations, presenting an ideal setting for unsupervised methods. With this motivation, we perform an unprecedented exploration into the large-scale discovery of recurring audio events in a diverse corpus of one million YouTube videos (45K hours of audio). Our approach is to apply a streaming, nonparametric...
Due to the opportunities provided by the Internet, people are taking advantage of e-learning courses and enormous research efforts have been dedicated to the development of e-learning systems. So far, many e-learning systems are proposed and used practically. However, in these systems the e-learning completion rate is low. One of the reasons is the low study desire and motivation. In this work, we...
The excessive use of the communication networks, rising of Internet of Things leads to increases the vulnerability to the important and secret information. advance attacking techniques and number of attackers are increasing radically. Intrusion is one of the main threats to the internet. Hence security issues had been big problem, so that various techniques and approaches have been presented to address...
With the development of web technology and human society, people accumulate more and more data on the Internet. It contains numerous resources in this mass of data. How to explore the use of these resources has become an urgent problem. If you analyze these data sets, you can extract the hidden information or discover new knowledge. The method to obtain useful information from computer and techniques...
Gathering the most relevant data for one's need, from the huge collection of data in the internet is a work of great difficult. To make it easier, we propose an application called text clustering, which is an automatic grouping of text documents into clusters, so that documents within a cluster defines the similarity between them, but they are not similar to documents in other clusters. Most of existing...
The graph-based algorithm for personalized recommendations mainly depends on the user-item model to construct a bipartite graph. We can provide recommendations by analyzing the bipartite graphs. However, for personalized videos recommendations, the classical recommendation algorithm based on graphs has low efficiency. Therefore, this paper gives an improved video recommendation algorithm that is based...
Podaj zakres dat dla filtrowania wyświetlonych wyników. Możesz podać datę początkową, końcową lub obie daty. Daty możesz wpisać ręcznie lub wybrać za pomocą kalendarza.