DataTone: Managing Ambiguity in Natural Language Interfaces for Data Visualization
By Tong Gao, Mira Dontcheva, Eytan Adar, Zhicheng Liu, K. G. Karahalios. ACM Symposium on User Interface Software and Technology, 2015
315 citations recorded by the source corpus.
Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems
View Paper: https://www.semanticscholar.org/paper/36a607d93637475a3675ee55ee7a1c2eb6d4376a
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Sahisnu Mazumder
- Bing Liu
- Shuai Wang
- Sepideh Esmaeilpour
- Michael S. Bernstein
- Mathis Petrovich
- Binbin Chen
- Bill Howe
In Computer Vision and Pattern Recognition
- Luc Van Gool
- Jitendra Malik
- Li Fei-Fei
- Cordelia Schmid
- Andrew Zisserman
- Michael J. Black
- Trevor Darrell
- Dacheng Tao
In Information Systems
- Shuai Wang
- Sahisnu Mazumder
- Sepideh Esmaeilpour
- Michael S. Bernstein
- Jeffrey Heer
- Diksha Khurana
- Sukhdev Singh
- Aditya Koli
Citations in the corpus
- Formalizing Visualization Design Knowledge as Constraints: Actionable and Extensible Models in Draco (2018, background): “Natural language interfaces may be better suited for communicating user intent [13, 53, 60], which could then be expressed as Draco constraints.”
- FLIN: A Flexible Natural Language Interface for Web Navigation (2020, unknown): “analysis (Setlur et al., 2016; Utama et al., 2018; Lawrence and Riezler, 2016; Gao et al., 2015), robot navigation (Artzi and Zettlemoyer, 2013; Tellex et al.”
- ChartDialogs: Plotting from Natural Language Instructions (2020, background): “This category of NLIs has been studied in Human Computer Interaction and related areas (Gao et al., 2015; Setlur et al., 2016; Srini-vasan and Stasko, 2017; Yu and Silva, 2019; Sun et al., 2010).”
- Distil : A Mixed-Initiative Model Discovery System for Subject Matter Experts ( Demo ) (2018, methodology): “Mixed-initiative analysis can be complemented by natural language interfaces such as those found in DataTone (Gao et al., 2015), Articulate (Sun et al., 2010), and Watson Analytics (IBM, 2018).”
- Empath: Understanding Topic Signals in Large-Scale Text (2016, background): “For example, researchers have automatically generated audio transitions for interviews, cued by signals of mood in the transcripts [34], dynamically generated soundtracks for novels using an emotional lexicon [6], or mapped ambiguous nat-ural language onto its visual meaning [12].”
- Natural language processing: state of the art, current trends and challenges (2017, methodology): “Some of the methods proposed by researchers to remove ambiguity is preserving ambiguity, e.g. (Shemtov 1997; Emele & Dorna 1998; Knight & Langkilde 2000; Tong Gao et al. 2015, Umber & Bajwa 2011) [39, 46, 65, 125, 139].”
- An Application-Independent Approach to Building Task-Oriented Chatbots with Interactive Continual Learning (2020, methodology): “Besides, [32, 41, 17, 14] built NLIs for visual data analysis.”
- TEMOS: Generating diverse human motions from textual descriptions (2022, background): “While, in theory, the more precise the description becomes, the less space there is for diversity; it is a desirable property for natural language interfaces to manage intrinsic ambiguities of linguistic expressions [12].”