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      A Method to Discover Digital Collaborative Conversations in Business Collaborations

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          Abstract

          Many companies have a suite of digital tools, such as Enterprise Social Networks, conferencing and document sharing software, and email, to facilitate collaboration among employees. During, or at the end of a collaboration, documents are often produced. People who were not involved in the initial collaboration often have difficulties understanding parts of its content because they are lacking the overall context. We argue there is valuable contextual and collaborative knowledge contained in these tools (content and use) that can be used to understand the document. Our goal is to rebuild the conversations that took place over a messaging service and their links with a digital conferencing tool during document production. The novelty in our approach is to combine several conversation-threading methods to identify interesting links between distinct conversations. Specifically we combine header-field information with social, temporal and semantic proximities. Our findings suggest the messaging service and conferencing tool are used in a complementary way. The primary results confirm that combining different conversation threading approaches is efficient to detect and construct conversation threads from distinct digital conversations concerning the same document.

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          SimBow at SemEval-2017 Task 3: Soft-Cosine Semantic Similarity between Questions for Community Question Answering

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            Conversation Threads Hidden within Email Server Logs

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              Author and article information

              Journal
              08 April 2019
              Article
              1905.06716
              36d6f3db-25dc-4084-93fc-cc56449dc78b

              http://arxiv.org/licenses/nonexclusive-distrib/1.0/

              History
              Custom metadata
              10th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management, May 2018, Seville, Spain
              cs.HC cs.CY cs.MA
              ccsd

              Applied computer science,Artificial intelligence,Human-computer-interaction

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