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Automated Text Summarization for the Enhancement of Public Services

Natural language processing and machine learning algorithms have been shown to be effective in a variety of applications. In this work, we contribute to the area of AI adoption in the public sector. We present an automated system that was used to process textual information, generate important keywords, and automatically summarize key elements of the Meadville community statements. We also describe the process of collaboration with My Meadville administrators during the development of our system. My Meadville, a community initiative, supported by the city of Meadville conducted a large number of interviews with the residents of Meadville during the community events and transcribed these interviews into textual data files. Their goal was to uncover the issues of importance to the Meadville residents in an attempt to enhance public services. Our AI system cleans and pre-processes the interview data, then using machine learning algorithms it finds important keywords and key excerpts from each interview. It also provides searching functionality to find excerpts from relevant interviews based on specific keywords. Our automated system allowed the city to save over 300 hours of human labor that would have taken to read all interviews and highlight important points. Our findings are being used by My Meadville initiative to locate important information from the collected data set for ongoing community enhancement projects, to highlight relevant community assets, and to assist in identifying the steps to be taken based on the concerns and areas of improvement identified by the community members.

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