Abstract
IT support is a vital and integral part of technology adoption. Conventionally, IT support service providers heavily rely on human effort and expertise to respond to user queries. Given the cost-benefit and 24 \(\times \) 7 availability for answering user questions, Virtual Assistants (VA) are highly applicable in the technical support domain. In this paper, we describe a novel methodology for building interactive virtual assistants for IT support using Dynamic Faceted Search (DFS). Given a question, dynamic facets are generated automatically, enabling the user to refine and narrow down their intent. To do so we leverage knowledge automatically induced from textual content and existing Semantic Web resources such as Wikidata. Such knowledge is then used to dynamically generate facets interactively based on the user’s responses as shown in the demo video (https://ibm.box.com/v/iswc2020-dfs). The experiments on two real-world datasets in the IT support domain show the effectiveness of DFS in refining the user’s queries and efficiently identifying possible solutions to their technical problems.
N. Mihindukulasooriya and R. Mahindru—Equal contributions.
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Notes
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A VA capable of fully automatic dialog generation is out of scope for DFS in the context of this work.
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For example, interactive problem diagnosis containing test and action steps; and process automation to invoke enterprise endpoints. for common questions.
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K = 5 in our experiments.
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0.41– 0.60 is considered as moderate [12].
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Mihindukulasooriya, N. et al. (2020). Dynamic Faceted Search for Technical Support Exploiting Induced Knowledge. In: Pan, J.Z., et al. The Semantic Web – ISWC 2020. ISWC 2020. Lecture Notes in Computer Science(), vol 12507. Springer, Cham. https://doi.org/10.1007/978-3-030-62466-8_42
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