NDLI: The Stability and Usability of Statistical Topic Models

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Issue 2(Regular Articles, Special Issue on Highlights of IUI 2015 (Part 2 of 2) and Special Issue on Highlights of ICMI 2014 (Part 1 of 2)), August 2016

Transfer Learning for Semisupervised Collaborative Recommendation

Agents Vs. Users: Visual Recommendation of Research Talks with Multiple Dimension of Relevance

The Effects of Interpersonal Attitude of a Group of Agents on User’s Presence and Proxemics Behavior

A Dynamic Pen-Based Interface for Writing and Editing Complex Mathematical Expressions With Math Boxes

The Stability and Usability of Statistical Topic Models

Minimal Interaction Content Discovery in Recommender Systems

Beyond the Touchscreen: An Exploration of Extending Interactions on Commodity Smartphones

Using Video to Automatically Detect Learner Affect in Computer-Enabled Classrooms

Teaching Social Communication Skills Through Human-Agent Interaction

Automatic Analysis of Naturalistic Hand-Over-Face Gestures

Using Respiration to Predict Who Will Speak Next and When in Multiparty Meetings

Issue 1(Special Issue on New Directions in Eye Gaze for Interactive Intelligent Systems (Part 2 of 2), Regular Articles and Special Issue on Highlights of IUI 2015 (Part 1 of 2)), May 2016

ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 5

ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 4

ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 3

ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 2

ACM Transactions on Interactive Intelligent Systems (TiiS) : Volume 1

The Stability and Usability of Statistical Topic Models

Content Provider	ACM Digital Library
Author	Pan, Shimei Lu, Jie Song, Yangqiu Yang, Yi Topkara, Mercan
Copyright Year	2016
Abstract	Statistical topic models have become a useful and ubiquitous tool for analyzing large text corpora. One common application of statistical topic models is to support topic-centric navigation and exploration of document collections. Existing work on topic modeling focuses on the inference of model parameters so the resulting model fits the input data. Since the exact inference is intractable, statistical inference methods, such as Gibbs Sampling, are commonly used to solve the problem. However, most of the existing work ignores an important aspect that is closely related to the end user experience: topic model stability. When the model is either re-trained with the same input data or updated with new documents, the topic previously assigned to a document may change under the new model, which may result in a disruption of end users’ mental maps about the relations between documents and topics, thus undermining the usability of the applications. In this article, we propose a novel user-directed non-disruptive topic model update method that balances the tradeoff between finding the model that fits the data and maintaining the stability of the model from end users’ perspective. It employs a novel constrained LDA algorithm to incorporate pairwise document constraints, which are converted from user feedback about topics, to achieve topic model stability. Evaluation results demonstrate the advantages of our approach over previous methods.
Starting Page	1
Ending Page	23
Page Count	23
File Format	PDF
ISSN	21606455
e-ISSN	21606463
DOI	10.1145/2954002
Volume Number	6
Issue Number	2
Journal	ACM Transactions on Interactive Intelligent Systems (TiiS)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-07-20
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	LDA Statistical topic model Constrained topic model Non-disruptive topic model update Stability Text analytics Usability
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Human-Computer Interaction

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Statistical topic models for multi-label document classification

User-directed Non-Disruptive Topic Model Update for Effective Exploration of Dynamic Content

Inferring Capabilities of Intelligent Agents from Their External Traits

Hierarchical classification with a topic taxonomy via LDA

Collaborative Language Models for Localized Query Prediction

LDA-Based Unified Topic Modeling for Similar TV User Grouping and TV Program Recommendation

Usability analysis with Markov models

Topic-aware social influence propagation models

Constrained recommendations for query visualizations

The Stability and Usability of Statistical Topic Models

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Statistical topic models for multi-label document classification

User-directed Non-Disruptive Topic Model Update for Effective Exploration of Dynamic Content

Inferring Capabilities of Intelligent Agents from Their External Traits

Hierarchical classification with a topic taxonomy via LDA

Collaborative Language Models for Localized Query Prediction

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The Stability and Usability of Statistical Topic Models