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 Chan, Cheng-wei


Sifu: Interactive Crowd-Assisted Language Learning

AAAI Conferences

This paper introduces SIFU, a system that recruits in real time native speakers as online volunteer tutors to help answer questions from Chinese language learners in reading news articles. SIFU integrates the strengths of two effective online language learning methods: reading online news and communicating with online native speakers. SIFU recruits volunteers from an online social network rather than recruits workers from Amazon Mechanical Turk.Initial experiments showed that the proposed approach is able to effectively recruit online volunteer tutors, adequately answer the learners' questions, and efficiently obtain an answer for the learner. Our field deployment illustrates that SIFU is very useful in assisting Chinese learners in reading Chinese news articles and online volunteer tutors are willing to help Chinese learners when they are on social network service.


MuSweeper: An Extensive Game for Collecting Mutual Exclusions

AAAI Conferences

Mutual exclusions provide useful information for learn- ing classes of concepts. We designed MuSweeper as a MineSweeper-like game to collect mutual exclusions from web users. Using the mechanism of an exten- sive game with Imperfect information, our experiments showed MuSweeper to collect mutual exclusions with high precision and efficiency.


Human Computation Game for Commonsense Data Verification

AAAI Conferences

Games With A Purpose (or GWAP) provide an interesting way to collect data from web users. With over a million sentences collected and growing steadily, data verification becomes increasingly important. This research explores the alternative of designing human computation games specifically for verification purposes. Two games, Top10 and Pirate and Ghost, are designed for commonsense data verification. Top10 is a single-player game, in which the player attempts to guess the top answers to a given question. We use the frequency data to verify if the assertion is truly common. Pirate and Ghost is a multiplayer guessing role playing game in a network of concepts from the CSKB. We use the game data to identify the relation between two concepts. This paper presents the design of both games, and evaluate the efficiency and precision of each with two experiments. The results show that the two games can be coupled to achiever higher efficiency and precision in the data verification process.