Semantically Driven Auto-completion
| Autor: | Konstantine Arkoudas, Mohamed Yahya |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
Information retrieval Parsing Computer Science - Computation and Language business.industry Computer science Usability Unstructured data 02 engineering and technology computer.software_genre Computer Science - Information Retrieval User experience design Analytics 020204 information systems 0202 electrical engineering electronic engineering information engineering Question answering 020201 artificial intelligence & image processing business Computation and Language (cs.CL) computer Information Retrieval (cs.IR) Natural language |
| Zdroj: | CIKM |
| Popis: | The Bloomberg Terminal has been a leading source of financial data and analytics for over 30 years. Through its thousands of functions, the Terminal allows its users to query and run analytics over a large array of data sources, including structured, semi-structured, and unstructured data; as well as plot charts, set up event-driven alerts and triggers, create interactive maps, exchange information via instant and email-style messages, and so on. To improve user experience, we have been building question answering systems that can understand a wide range of natural language constructions for various domains that are of fundamental interest to our users. Such natural language interfaces, while exceedingly helpful to users, introduce a number of usability challenges of their own. We tackle some of these challenges through auto-completion for query formulation. A distinguishing mark of our auto-complete systems is that they are based on and guided by corresponding semantic parsing systems. We describe the auto-complete problem as it arises in this setting, the novel algorithms that we use to solve it, and report on the quality of the results and the efficiency of our approach. 12 pages, under submission |
| Databáze: | OpenAIRE |
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