With increased recognition and understanding of how exceptionalities can affect a child’s development and education has come a seemingly inevitable increase in the number and complexity of useful interventions. These interventions often address not only classroom behaviors and learning but also the child’s life outside of the classroom. As a result, multidisciplinary teams involving school system personnel, parents, and others are essential.
Current best practices for services to children with disabilities include the use of a multidisciplinary team and the active involvement of families. What are the advantages of this approach? What challenges might occur and if you were a classroom teacher, how would you help address the challenges?
“How can recommendation systems guide the generation of personalized movie trailers, and how effective is personalization in movie trailers?” The purpose of this study is to propose a framework for personalized movie trailers based on consumer preferences, and to provide empirical evidence for the effectiveness of such a trailer for audiences. 1.3 Academic relevance Numerous studies in the field of video summarization or video abstraction have been conducted. Video summarization systems select significant segments for users to generate a short version of a lengthy video (Kannan, Ghinea, & Swaminathan, 2015). Existing approaches can be classified into cognitive-level and affective-level approaches, the former extracting low-level features such as color, motion, and composition, and the latter utilizing high-level semantic features such as events and semantic concepts. Most of these approaches focus on analyzing genre-specific movie trailers for patterns to automatically select salient moments in a movie for a movie trailer (Hermes & Schultz, 2006; Smeaton, Lehane, O’Connor, Brady, & Craig, 2006; Smith, Joshi, Huet, Hsu, & Cota, 2017), thus generating a generic summary that is common for all users. Fewer research has been done with regards to personalizing video summarization. One highly relevant study is by Kannan, Ghinea, and Swaminathan (2015), who propose a novel system that summarizes a movie based on the preferences and interests of the user. Shots and scenes are automatically detected, which are labeled with high-level features. A key difference between this system and the proposed system in this study is the collection of user preferences, which are asked explicitly to the user in order to generate a summary, while in this study user preferences are inferred through existing data.>GET ANSWER