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Full-Text Articles in Computer Engineering
Querie: Collaborative Database Exploration, Magdalini Eirinaki, Suju Abraham, Neoklis Polyzotis, Naushin Shaikh
Querie: Collaborative Database Exploration, Magdalini Eirinaki, Suju Abraham, Neoklis Polyzotis, Naushin Shaikh
Magdalini Eirinaki
Interactive database exploration is a key task in information mining. However, users who lack SQL expertise or familiarity with the database schema face great difficulties in performing this task. To aid these users, we developed the QueRIE system for personalized query recommendations. QueRIE continuously monitors the user’s querying behavior and finds matching patterns in the system’s query log, in an attempt to identify previous users with similar information needs. Subsequently, QueRIE uses these “similar” users and their queries to recommend queries that the current user may find interesting. In this work we describe an instantiation of the QueRIE framework, where …
Feature-Based Opinion Mining And Ranking, Magdalini Eirinaki, S. Pisal, J. Singh
Feature-Based Opinion Mining And Ranking, Magdalini Eirinaki, S. Pisal, J. Singh
Magdalini Eirinaki
The proliferation of blogs and social networks presents a new set of challenges and opportunities in the way information is searched and retrieved. Even though facts still play a very important role when information is sought on a topic, opinions have become increasingly important as well. Opinions expressed in blogs and social networks are playing an important role influencing everything from the products people buy to the presidential candidate they support. Thus, there is a need for a new type of search engine which will not only retrieve facts, but will also enable the retrieval of opinions. Such a search …
Identification Of Influential Social Networkers, Magdalini Eirinaki, S. P. Singh Monga, S. Sundaram
Identification Of Influential Social Networkers, Magdalini Eirinaki, S. P. Singh Monga, S. Sundaram
Magdalini Eirinaki
Online social networking is deeply interleaved in today's lifestyle. People come together and build communities to share thoughts, offer suggestions, exchange information, ideas, and opinions. Moreover, social networks often serve as platforms for information dissemination and product placement or promotion through viral marketing. The success rate in this type of marketing could be increased by targeting specific individuals, called 'influential users', having the largest possible reach within an online community. In this paper, we present a method aiming at identifying the influential users within an online social networking application. We introduce ProfileRank, a metric that uses popularity and activity characteristics …
Mining Frequent Generalized Patterns For Web Personalization In The Presence Of Taxonomies, Panagiotis Giannikopoulos, Iraklis Varlamis, Magdalini Eirinaki
Mining Frequent Generalized Patterns For Web Personalization In The Presence Of Taxonomies, Panagiotis Giannikopoulos, Iraklis Varlamis, Magdalini Eirinaki
Magdalini Eirinaki
The Web is a continuously evolving environment, since its content is updated on a regular basis. As a result, the traditional usage-based approach to generate recommendations that takes as input the navigation paths recorded on the Web page level, is not as effective. Moreover, most of the content available online is either explicitly or implicitly characterized by a set of categories organized in a taxonomy, allowing the page-level navigation patterns to be generalized to a higher, aggregate level. In this direction, the authors present the Frequent Generalized Pattern (FGP) algorithm. FGP takes as input the transaction data and a hierarchy …
Web Site Personalization Based On Link Analysis And Navigational Patterns, Magdalini Eirinaki, Michalis Vazirgiannis
Web Site Personalization Based On Link Analysis And Navigational Patterns, Magdalini Eirinaki, Michalis Vazirgiannis
Magdalini Eirinaki
The continuous growth in the size and use of the World Wide Web imposes new methods of design and development of online information services. The need for predicting the users' needs in order to improve the usability and user retention of a Web site is more than evident and can be addressed by personalizing it. Recommendation algorithms aim at proposing “next” pages to users based on their current visit and past users' navigational patterns. In the vast majority of related algorithms, however, only the usage data is used to produce recommendations, disregarding the structural properties of the Web graph. Thus …
Web Mining For Web Personalization, Magdalini Eirinaki, Michalis Vazirgiannis
Web Mining For Web Personalization, Magdalini Eirinaki, Michalis Vazirgiannis
Magdalini Eirinaki
Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user's navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content, and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization …