Physical Sciences and Mathematics Commons^™

Using Google Tag Manager And Google Analytics, (Code{4}Lib Journal), Suzanna Conrad

Inaugural CSU IR Conference, 2015

Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona

What’S New Since The April 2013 Stim Ir Subcommittee Report To Cold: Hydra, Islandora And Dspace, Aaron Collier, Suzanna Conrad, Carmen Mitchell, Joan Parker, Andrew Weiss, Jeremy C. Shellhase

Inaugural CSU IR Conference, 2015

Aaron Collier, Digital Repository Services Manager, Chancellor’s Office
Suzanna Conrad, Digital Initiatives Librarian, Cal Poly Pomona
Carmen Mitchell, Institutional Repository Librarian, CSU San Marcos
Joan Parker, Librarian, Moss Landing Marine Laboratories
Andrew Weiss, Digital Services Librarian, CSU Northridge

Jeremy Shellhase, Head of Information Services & Systems Department, Humboldt State University

The State Of Scholarworks, Aaron Collier

Inaugural CSU IR Conference, 2015

Aaron Collier, Digital Repository Services Manager, Chancellor’s Office

Querie: Collaborative Database Exploration, Magdalini Eirinaki, Suju Abraham, Neoklis Polyzotis, Naushin Shaikh

Faculty Publications

No abstract provided.

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

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

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 …

Sql Querie Recommendations: A Query Fragment-Based Approach, Jayad Akbarnejad, Magdalini Eirinaki, Suju Koshy, Duc On, Neoklis Polyzotis

Faculty Publications

Relational database systems are becoming increasingly popular in the scientific community to support the interactive exploration of large volumes of data. In this scenario, users employ a query interface (typically, a web-based client) to issue a series of SQL queries that aim to analyze the data and mine it for interesting information. First-time users, however, may not have the necessary knowledge to know where to start their exploration. Other times, users may simply overlook queries that retrieve important information. In this work we describe a framework to assist non-expert users by providing personalized query recommendations. The querying behavior of the …

Personal Vs. Social, Magdalini Eirinaki

Faculty Publications

The last few years we witnessed an impressive growth in social networks and in applications that add value to their amassed information. At the same time, the continuing expansion of mobile platforms and applications (e.g. iPhone), combined with the overwhelming supply of information and services, makes effective personalization and context-awareness much required features. One may consider "personal" and "social" data management as comprising two distinct directions with conflicting characteristics. However, it can be argued that they complement each other and that in future applications they will ultimately converge. This "personal vs. social" predicament presents a number of interesting topics that …

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 …

Selfish Wavelength Assignment In Multifiber Optical Networks, Evangelos Bampas, Aris Pagourtzis, George Pierrakos, Katerina Potika

Faculty Publications, Computer Science

No abstract provided.

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 …

Loss Aware Rate Allocations In H.263 Coded Video Transmissions, Xiao Su, Benjamin Wah

Faculty Publications

For packet video, information loss and bandwidth limitation are two factors that affect video playback quality. Traditional rate allocation approaches have focused on optimizing video quality under bandwidth constraint alone. However, in the best-effort Internet, packets carrying video data are susceptible to losses, which need to be reconstructed at the receiver side. In this paper, we propose loss aware rate allocations in both group-of-block (GOB) level and macroblock level, given that certain packets are lost during transmissions and reconstructed using simple interpolation methods at the receiver side. Experimental results show that our proposed algorithms can produce videos of higher quality …

The Igipi Ontological Framework: Integrating Gene Interactions With Protein Interactions, Bill Andreopoulos, Aijun An, Xiangji Huang

Faculty Publications, Computer Science

No abstract provided.

Ontologies In Web Personalization, Magdalini Eirinaki, Michalis Vazirgiannis

Faculty Publications

No abstract provided.

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 …

An Interpretation Of Martian Thermospheric Waves Based On Analysis Of A General Circulation Model, Manoj Joshi, Jeffery Hollingsworth, Robert Haberle, Alison Bridger

Faculty Publications, Meteorology and Climate Science

Planetary‐scale longitudinal variations in density observed by the Mars Global Surveyor accelerometer in the 125 km region can be qualitatively reproduced by the NASA Ames Mars general circulation model in the 80 km altitude region, but only when locations having specific local times are used in the analysis. If the model results are averaged over all local times, the high‐altitude longitudinal variations nearly disappear, leaving only a small stationary wave 1 pattern, consistent with theory and previous modeling studies. This analysis suggests that the observed wavelike structures are a result of sampling tidal modes at a limited range of local …