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Can I read Koko: a System for Scalable Semantic Querying of Text on EtoBox?
Koko: a System for Scalable Semantic Querying of Text by Xiaolan Wang; Jiyu Komiya; Yoshihiko Suhara; Aaron Feng; Behzad Golshan; Alon Halevy; Wang-Chiew Tan is a Computer Science article available to read on EtoBox.
What is Koko: a System for Scalable Semantic Querying of Text about?
K oko is a declarative information extraction system that incorporates advances in natural language processing techniques in its extraction language. K oko 's extraction language supports simultaneous specification of conditions over the surface syntax and on the structure of the dependency parse tree of sentences, thereby allowing for more refined extractions. Furthermore, the K oko extraction language allows for aggregating evidence from an input document and supports conditions that are tolerant of linguistic variation of expressing concepts. In this demo, we outline the design of K oko , a system for extracting information and understanding the results of the extraction. K oko provides an interactive interface that allows participants to write queries, understand the input and results of the queries. In particular, the user can customize the input text, visualize the input text's dependency parse trees, and understand the correspondences between query components, dependency tree nodes, text tokens, and the computation and associated scores that led to an extraction.
Who reads Koko: a System for Scalable Semantic Querying of Text?
It is typically read by researchers, students, and practitioners in Computer Science.
- Author
- Xiaolan Wang; Jiyu Komiya; Yoshihiko Suhara; Aaron Feng; Behzad Golshan; Alon Halevy; Wang-Chiew Tan
- Published
- 2018
- Language
- EN
- Field
- Computer Science (Physical Sciences)