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- W2897540080 abstract "Software support tickets contain short and noisy text from the customers. Software products are often represented by various surface forms and informal abbreviations. Automatically identifying software mentions from support tickets and determining the official names and versions are helpful for many downstream applications, eg routing the support tickets to the right expert groups for support. In this work, we study the problem ofsoftware product name extraction andlinking from support tickets. We first annotate and analyze sampled tickets to understand the language patterns. Next, we design features using local, contextual, and external information sources, for extraction and linking models. In experiments, we show that linear models with the proposed features are able to deliver better and more consistent results, compared with the state-of-the-art baseline models, even on dataset with sparse labels." @default.
- W2897540080 created "2018-10-26" @default.
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- W2897540080 date "2018-10-17" @default.
- W2897540080 modified "2023-09-25" @default.
- W2897540080 title "Towards Effective Extraction and Linking of Software Mentions from User-Generated Support Tickets" @default.
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- W2897540080 doi "https://doi.org/10.1145/3269206.3272026" @default.
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