Community research partnership: A case study of San Antonio Research Partnership Portal

Abstract

Research collaboration between academic researchers from universities, organizations and government local city departments can be tremendously useful to all institutions, but these collaborations involve a wide range of skill sets, making them difficult to establish and manage. For many local government city departments, finding research professionals and collaborators to solve community problems remains a big challenge. The information of research opportunities is either posted on the individual city department website or researchers are approached through a personal relationship with city department officials. As a result, a researcher interested in working with the city department would have to either navigate various websites or try to build a personal contact with city department officials. In this paper, we will look at the relevance of community research partnerships as well as the barriers that prevent them. We will also demonstrate the development of, Research Partnership Portal, a collaborative platform for academic researchers, organizations, and government city departments in San Antonio. This portal will assist academic researchers and organizations in collaborating with government city departments and using current administrative data to produce effective answers to community concerns.

A Comparative Assessment of Unsupervised Keyword Extraction Tools

“…There is an attempt to evaluate KE tools on different benchmark datasets by Nadim et al to show that the integration of KE tools with different applications can significantly increase productivity, accuracy, and scalability [18]. They conducted their experiment on San Antonio Research Partnership Portal as a use case to develop different web applications that can use KE tools to increase productivity and scalability [33]. Other literature worked on evaluating KE methods for different data domains like painting archives [34], new multi-document benchmark datasets [35], similarity in news articles [36], and indexing news articles [17].…”