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Product attribute extraction based real-time c2c matching of microblogging messages.

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dc.contributor.author Mohamed Rilji, MR
dc.contributor.author Bandara, HMND
dc.contributor.author Ranathunga, S
dc.contributor.editor Narayana, M
dc.contributor.editor Chathuranga, D
dc.date.accessioned 2023-04-24T09:41:26Z
dc.date.available 2023-04-24T09:41:26Z
dc.date.issued 2018-05
dc.identifier.citation ************ en_US
dc.identifier.uri http://dl.lib.uom.lk/handle/123/20939
dc.description.abstract We describe a solution for real-time matching of microblogging messages related to product selling or buying. C2C buy/sell interest matching in real time is nontrivial due to the complexities of interpreting social media messages, number of messages, and diversity of products/services. Therefore, we adopt a combination of techniques from natural language processing, complex event processing, and distributed systems. First, we convert the message into semantics using named-entity recognition with CRF and Logistic Regression. Then the extracted data are matched using a complex event processor. Moreover, NoSQL and inmemory computing are used to enhance the scalability and performance. The proposed solution shows a high accuracy where classification and CRF models recorded an accuracy of 98.5% and 82.07% when applied to a real-world dataset. Low latency was observed for information extraction, in-memory data manipulation, and complex event processing were latencies were 0.5 ms, 5 ms, and 3.6 ms, respectively. en_US
dc.language.iso en en_US
dc.title Product attribute extraction based real-time c2c matching of microblogging messages. en_US
dc.type Conference-Abstract en_US
dc.identifier.faculty Engineering en_US
dc.identifier.department Engineering Research Unit, Faculty of Engineering, University of Moratuwa en_US
dc.identifier.year 2018 en_US
dc.identifier.conference ERU Symposium 2018 en_US
dc.identifier.place Moratuwa, Sri Lanka en_US
dc.identifier.proceeding Proceedings of the ERU Symposium 2018 en_US


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