Improving Recommendation Quality by Merging Collaborative Filtering and Social Relationships

Matrix Factorization techniques have been successfully applied to raise the quality of suggestions generated\ud by Collaborative Filtering Systems (CFSs). Traditional CFSs\ud based on Matrix Factorization operate on the ratings provided\ud by users and have been recently extended to incorporate\ud demographic aspects such as age and gender. In this paper we\ud propose to merge CF techniques based on Matrix Factorization\ud and information regarding social friendships in order to\ud provide users with more accurate suggestions and rankings\ud on items of their interest. The proposed approach has been\ud evaluated on a real-life online social network; the experimental\ud results show an improvement against existing CF approaches.\ud A detailed comparison with related literature is also presen

Session B-2: Pirates: Past and Present

Piracy has endured for as long as maritime trade has existed. From the ancient Mediterranean world to the modern-day Somali coast, pirates have threatened merchant ships. The legacy of piracy has inspired countless songs, poems, novels, and movies. Who were pirates? What did they want? Where did they go? How did they interact with states? Students have internalized stereotypes about pirates from popular culture, but rarely consider these questions about piracy. This workshop will examine the significance of piracy in world history through texts and visual material. Case studies will be global, but focus on the early modern period

Spartan Daily, April 24, 1951

Volume 39, Issue 126https://scholarworks.sjsu.edu/spartandaily/11547/thumbnail.jp

Bringing the Field into the Classroom by Using Dynamic Digital Maps to Engage Undergraduate Students in Petrology Research

This article describes the use of Dynamic Digital Maps (DDMs) in undergraduate petrology courses. A DDM is a stand-alone computer program that presents interactive geologic maps, digital images, movies, animations, text and data. DDMs were developed for use in two undergraduate research projects, and impacts on student learning were evaluated by administering assessments on students before and after participation in one of the projects. Researchers found significant gains in both students' confidence in their ability to do research and to understand petrology, and noted that DDMs are versatile and can potentially be adapted effectively from 100-level introductory geology labs to research-oriented gradute level courses and in a variety of geologic subdisciplines. Educational levels: Graduate or professional, Graduate or professional

Escaping in the “Tender, Blue Haze of Evening”: The Morro Castle and Cruising as a Form of Leisure in 1930s America

The paper demonstrates a microhistory approach to the development of cruising as a form of leisure in the early twentieth century of American history. Using the 1934 Morro Castle disaster and the subsequent attention the ship and its survivors received, this paper provides a window into an unexplored topic of American leisure. This paper is unique in its finding because the disaster provided numerous firsthand accounts of cruising in the 1930s. The findings illustrate that this form of leisure was directly connected to larger events and trends of the time, including the Great Depression, Prohibition, and America’s Cuban connection. Cruising as a form of leisure, thus, developed out of a social and cultural demand, illustrating escapism in a tumultuous period

Spartan Daily, October 16, 2013

Volume 141, Issue 21https://scholarworks.sjsu.edu/spartandaily/1440/thumbnail.jp

Spartan Daily, October 16, 2013

Volume 141, Issue 21https://scholarworks.sjsu.edu/spartandaily/1440/thumbnail.jp

Spartan Daily, October 16, 2013

Volume 141, Issue 21https://scholarworks.sjsu.edu/spartandaily/1440/thumbnail.jp

Inferring Interpersonal Relations in Narrative Summaries

Characterizing relationships between people is fundamental for the understanding of narratives. In this work, we address the problem of inferring the polarity of relationships between people in narrative summaries. We formulate the problem as a joint structured prediction for each narrative, and present a model that combines evidence from linguistic and semantic features, as well as features based on the structure of the social community in the text. We also provide a clustering-based approach that can exploit regularities in narrative types. e.g., learn an affinity for love-triangles in romantic stories. On a dataset of movie summaries from Wikipedia, our structured models provide more than a 30% error-reduction over a competitive baseline that considers pairs of characters in isolation