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Student codes rental recommendation system, wins research award

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Tsai Chih-ying (蔡姿瑩), a graduate researcher with National Chi Nan University’s (NCNU) Department of Computer Science and Information Engineering, has created a tailored solution for banishing housing woes from the university community. For streamlining the data and user experience and creating suitable balances to check this recommendation-based system, the student developer received a research accolade from the Ministry of Science and Technology.

NCNU is situated on Puli Township’s Taomi Plateau, and an annual average of 3,000 students opt for off-campus housing, which are only available in the surrounding neighborhoods below. Such mountainside options, however, are complicated by homeowners and realtors cross-posting the same messages across several forums and social media, often in different formats and with a wide range of uneven demands.

Tsai was confronted with the same gaggle of disparate information when she transferred from Tunghai University to NCNU in sophomore year. Dismayed by the lack of consistency, including non-uniform standards for charging a percentage fee on certain platforms for using their services, the student coder decided to develop her own system and recruited the help of Lin Shian-hua (林宣華), an associate professor with NCNU focusing on web data and social network mining, information extraction, mobile applications, and digital learning systems.

In developing this platform integrating rental data, mapping technology, and real-time feedback, Tsai and Lin are led by their vision of serving the end-users — the university community. To prevent reviews from being distorted by malicious users such as those polluting Facebook and Google’s ecosystems, their platform requires real-name registration and account logins can only be accessed by on-campus intranet. This ensures the integrity of rental reviews and upholds accountability.

The quality of information is equally important to the performance of the platform, and popular sources such as long-running Facebook groups and rental websites were vetted before being added to the NCNU network. Moreover, Tsai and Lin applied lexical analysis, tokenization, noun recognition, syntax analysis, and comparative modeling to help users like everyday students find their right rental fit with relative ease and a high degree of accuracy.

As for every renter’s worst, reoccurring nightmare — the impossible divide between what was shared online and what the property actually offers in real life, the two NCNU developers decided to rely on an accountable endorsement system to provide more transparency and combat such malpractices. An algorithm compiles top lists viewable on mobile, in which positive feedback bolsters rankings and negative reviews devalue a property’s desirability. Postings that do not follow community guidelines are docked as well.

Professor Lin explains that while the programming technology used by Tsai may not be the most advanced, what was uniquely innovative about her plan was the detailed vision Tsai had for the user experience. In addition to overlaying the locations of active convenience stores, grocery shops, pharmacies, and other service providers, her tailored map shows bus stops, the latest routes, and other avenues for transportation.

“Many information engineers from NCNU are quickly recruited by established Taiwanese firms like TSMC upon graduation,” says Lin, noting that having an environment conducive to research and paper-writing is the key to securing grants and awards from the public education system. These accolades are equally applicable to academic and corporate careers, “for coding will become a basic skillset carried by the future workforce.”

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