On content-based recommendation and user privacy in social-tagging systems

Recommendation systems and content filtering approaches based on annotations and ratings, essentially rely on users expressing their preferences and interests through their actions, in order to provide personalised content. This activity, in which users engage collectively has been named social tagging, and it is one of the most popular in which users engage online, and although it has opened new possibilities for application interoperability on the semantic web, it is also posing new privacy threats. It, in fact, consists of describing online or offline resources by using free-text labels (i.e. tags), therefore exposing the user profile and activity to privacy attacks. Users, as a result, may wish to adopt a privacy-enhancing strategy in order not to reveal their interests completely. Tag forgery is a privacy enhancing technology consisting of generating tags for categories or resources that do not reflect the user's actual preferences. By modifying their profile, tag forgery may have a negative impact on the quality of the recommendation system, thus protecting user privacy to a certain extent but at the expenses of utility loss. The impact of tag forgery on content-based recommendation is, therefore, investigated in a real-world application scenario where different forgery strategies are evaluated, and the consequent loss in utility is measured and compared.Peer ReviewedPostprint (author’s final draft

Bandit algorithms in recommender systems

Peer reviewe

Использование формализированных информационных понятий в формировании профессиональной компетентности будущих операторов компьютерного набора

Розглянуто підхід формалізації понять інформатики як науки про інформацію навколишнього світу. Запропоновані основні формалізовані поняття інформатики.Рассмотрен подход формализации понятий информатики как науки об информации окружающего мира. Предложены основные формализованные понятия информатики

Web Page Ranking Based on Text Content and Link Information Using Data Mining Techniques

Thanks to the rapid expansion of the Internet, anyone can now access a vast array of information online. However, as the volume of web content continues to grow exponentially, search engines face challenges in delivering relevant results. Early search engines primarily relied on the words or phrases found within web pages to index and rank them. While this approach had its merits, it often resulted in irrelevant or inaccurate results. To address this issue, more advanced search engines began incorporating the hyperlink structures of web pages to help determine their relevance. While this method improved retrieval accuracy to some extent, it still had limitations, as it did not consider the actual content of web pages. The objective of the work is to enhance Web Information Retrieval methods by leveraging three key components: text content analysis, link analysis, and log file analysis. By integrating insights from these multiple data sources, the goal is to achieve a more accurate and effective ranking of relevant web pages in the retrieved document set, ultimately enhancing the user experience and delivering more precise search results the proposed system was tested with both multi-word and single-word queries, and the results were evaluated using metrics such as relative recall, precision, and F-measure. When compared to Google’s PageRank algorithm, the proposed system demonstrated superior performance, achieving an 81% mean average precision, 56% average relative recall, and a 66% F-measure

IT based social media impacts on Indonesian general legislative elections 2014

The information technology applications in cyberspace (the internet) are currently dominated by social media. The author investigates and explores the advantages of social media implementation of any political party in Indonesian general legislative elections 2014. There are twelve national political parties participating in the election as contestants plus three local political parties in Aceh. In this research, author focus on national political parties only. The author visited, analyzed, and learnt the social media used by the contestants. Those social media are : 1) Facebook, 2) Twitter, and 3) YouTube. Author also compares the popularity of political parties on social media with the results of a real count. Then Author can discuss : 1) the impact of social media on political parties, 2) social media as a brand of political parties, 3) social media as political presentation, and 4) social media as virtual society. The results of this study indicate that Facebook is still a social media application that received high attention by the voters on a campaign of political parties. Indonesian's legislative elections won by parties that are using social media as part of their campaigns.Comment: 14 page

CONTENT BASED RETRIEVAL OF LECTURE VIDEO REPOSITORY: LITERATURE REVIEW

Multimedia has a significant role in communicating the information and a large amount of multimedia repositories make the browsing, retrieval and delivery of video contents. For higher education, using video as a tool for learning and teaching through multimedia application is a considerable promise. Many universities adopt educational systems where the teacher lecture is video recorded and the video lecture is made available to students with minimum post-processing effort. Since each video may cover many subjects, it is critical for an e-Learning environment to have content-based video searching capabilities to meet diverse individual learning needs. The present paper reviewed 120+ core research article on the content based retrieval of the lecture video repositories hosted on cloud by government academic and research organization of India