BEGIN:VCALENDAR PRODID:-//Faculty of Computer Science//Events Calendar//EN VERSION:2.0 CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20180814T173129Z DTSTART:20171204T140000Z SUMMARY:MCSc Thesis Defence - Fast Calculation of N-Gram-Based Phrase Similarity DESCRIPTION:When: December 4\, 2017 @ 10:00 am\n \nWho: Zichu Ai\nTitle: Fast Calculation of N-Gram-Based Phrase Similarity\nExamining Committee:\nNorbert Zeh - Faculty of Computer Science (Supervisor)\nAbidalrahman Mohammad - Faculty of Computer Science (Co-Supervisor)\nVlado Keselj - Faculty of Computer Science (Reader)\nEvangelos Milios - Faculty of Computer Science (Reader)\nChair: Raghav Sampangi - Faculty of Computer Science\nAbstract:\nText Relatedness using word and phrase relatedness method (TrWP) is a text relatedness measure that computes semantic similarity between words and phrases utilizing aggregated statistics from the Google Web-1T corpus. The phrase similarity computation in TrWP has signicant overhead in time and memory cost\, making TrWP impractical for real-world usage. This thesis presents an in-memory computational framework for TrWP\, which optimizes the calculation process by ecient indexing and compact storage using perfect hashing\, parallelism\, quantization and variable length encoding. Using the Google Web 1T 5-gram corpus\, we demonstrate that the computational speed of our framework outperforms the le-based TrWP framework by 5 to 6 orders of magnitude. LOCATION:Room 311\, Goldberg Computer Science Building URL:https://www.dal.ca/faculty/computerscience/news-events/events/2017/12/04/mcsc_thesis_defence___fast_calculation_of_n_gram_based_phrase_similarity.html UID:https://www.dal.ca/faculty/computerscience/news-events/events/2017/12/04/mcsc_thesis_defence___fast_calculation_of_n_gram_based_phrase_similarity/_jcr_content/contentPar/dcalfacultyevent.html END:VEVENT END:VCALENDAR