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| Autor: | Aarsh Prakash Agarwal, Iftikhar Ahamath Burhanuddin, Harvineet Singh, Gaurav Verma, Aadhavan M. Nambhi, Bhanu Prakash Reddy |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Topic model business.industry Process (engineering) Computer science Computer Science - Human-Computer Interaction Recommender system Computer Science - Information Retrieval Human-Computer Interaction (cs.HC) Task (project management) Software analytics Software Human–computer interaction Domain knowledge Leverage (statistics) business Information Retrieval (cs.IR) |
| Zdroj: | UMAP |
| DOI: | 10.1145/3320435.3320477 |
| Popis: | Data analytics software applications have become an integral part of the decision-making process of analysts. Users of such a software face challenges due to insufficient product and domain knowledge, and find themselves in need of help. To alleviate this, we propose a task-aware command recommendation system, to guide the user on what commands could be executed next. We rely on topic modeling techniques to incorporate information about user's task into our models. We also present a help prediction model to detect if a user is in need of help, in which case the system proactively provides the aforementioned command recommendations. We leverage the log data of a web-based analytics software to quantify the superior performance of our neural models, in comparison to competitive baselines. Comment: 27th Conference on User Modeling, Adaptation and Personalization (UMAP'19) |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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