NDLI: Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts

Please wait, while we are loading the content...

Ten Years of Wisdom

Enterprise Employee Training via Project Team Formation

Learning Parametric Models for Context-Aware Query Auto-Completion via Hawkes Processes

Neural Models for Full Text Search

Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts

Keeping Apace with Progress in Natural Language Processing

Task-Guided and Path-Augmented Heterogeneous Network Embedding for Author Identification

Joint Deep Modeling of Users and Items Using Reviews for Recommendation

Machine Learning at Amazon

Online Actions with Offline Impact: How Online Social Networks Influence Online and Offline User Behavior

Statistical Spoken Dialogue Systems and the Challenges for Machine Learning

Primum Non Nocere: Healthcare In The Digital Age

Managing Risk of Bidding in Display Advertising

Real-Time Bidding by Reinforcement Learning in Display Advertising

Unsupervised Ranking using Graph Structures and Node Attributes

Harnessing the Power of Data Science through Research

Neural Text Embeddings for Information Retrieval

Workshop on Scholarly Web Mining (SWM 2017)

WSDM Cup 2017: Vandalism Detection and Triple Scoring

Beyond Query Logs: Recommendation and Evaluation

iPhone's Digital Marketplace: Characterizing the Big Spenders

Does Document Relevance Affect the Searcher's Perception of Time?

PRED: Periodic Region Detection for Mobility Modeling of Social Media Users

Beyond the Words: Predicting User Personality from Heterogeneous Information

Multi-Product Utility Maximization for Economic Recommendation

Social Incentive Optimization in Online Social Networks

Predicting Online Purchase Conversion for Retargeting

Deep Memory Networks for Attitude Identification

Unbiased Learning-to-Rank with Biased Feedback

Utilizing Knowledge Graphs in Text-centric Information Retrieval

Mining Actionable Insights from Social Networksat WSDM 2017

Recommender Systems: Research Direction

Raising Graphs From Randomness to Reveal Information Networks

Generating Illustrative Snippets for Open Data on the Web

Applying Space Syntax to Online Mapping Tools

German Typographers vs. German Grammar: Decomposition of Wikipedia Category Labels into Attribute-Value Pairs

Groove Radio: A Bayesian Hierarchical Model for Personalized Playlist Generation

Counting Graphlets: Space vs Time

Motifs in Temporal Networks

D-Cube: Dense-Block Detection in Terabyte-Scale Tensors

Learning from User Interactions in Personal Search via Attribute Parameterization

Social Media Anomaly Detection: Challenges and Solutions

1st International Workshop on Search and Mining Terrorist Online Content & Advances in Data Science for Cyber Security and Risk on the Web

Modeling Source Code to Support Retrieval-Based Applications

How Smart Does Your Profile Image Look?: Estimating Intelligence from Social Network Profile Images

Investigation of User Search Behavior While Facing Heterogeneous Search Services

Semantic-aware Query Processing for Activity Trajectories

Comparative Document Analysis for Large Text Corpora

Temporally Factorized Network Modeling for Evolutionary Network Analysis

Representation Learning with Pair-wise Constraints for Collaborative Ranking

Modeling Air Travel Choice Behavior with Mixed Kernel Density Estimations

Modeling Document Networks with Tree-Averaged Copula Regularization

Delving Deep into Personal Photo and Video Search

WSDM 2017 Workshop on Mining Online Health Reports: MOHRS 2017

Scalable Text Analysis

Anticipating Information Needs Based on Check-in Activity

Click Through Rate Prediction for Local Search Results

Constructing and Embedding Abstract Event Causality Networks from Text Snippets

Not Enough Data?: Joint Inferring Multiple Diffusion Networks via Network Generation Priors

Location Influence in Location-based Social Networks

Multilinear Factorization Machines for Multi-Task Multi-View Learning

Quantifying and Bursting the Online Filter Bubble

RedQueen: An Online Algorithm for Smart Broadcasting in Social Networks

Document Retrieval Model Through Semantic Linking

Fun Facts: Automatic Trivia Fact Extraction from Wikipedia

Online Matrix Completion for Signed Link Prediction

Probabilistic Social Sequential Model for Tour Recommendation

Algorithms for Active Classifier Selection: Maximizing Recall with Precision Constraints

New Probabilistic Models for Recommender Systems with Rich Contextual and Content Information

Uncovering the Dynamics of Crowdlearning and the Value of Knowledge

A Concise Integer Linear Programming Formulation for Implicit Search Result Diversification

Related Event Discovery

Social Collaborative Viewpoint Regression with Explainable Recommendations

Trustworthy Analysis of Online A/B Tests: Pitfalls, challenges and solutions

DiSMEC: Distributed Sparse Machines for Extreme Multi-label Classification

Mining Medical Causality for Diagnosis Assistance

Leveraging Behavioral Factorization and Prior Knowledge for Community Discovery and Profiling

A Comparison of Document-at-a-Time and Score-at-a-Time Query Evaluation

Lightweight Multilingual Entity Extraction and Linking

Recurrent Recommender Networks

Learning Sensitive Combinations of A/B Test Metrics

Label Informed Attributed Network Embedding

Adapting Information Retrieval to User Signals via Stochastic Models

Reducing Controversy by Connecting Opposing Views

ANNE: Improving Source Code Search using Entity Retrieval Approach

Predicting Completeness in Knowledge Bases

Bartering Books to Beers: A Recommender System for Exchange Platforms

Embedding of Embedding (EOE): Joint Embedding for Coupled Heterogeneous Networks

Modeling Navigation in Information Networks

Detecting and Characterizing Eating-Disorder Communities on Social Media

Partitioning and Segment Organization Strategies for Real-Time Selective Search on Document Streams

Synthesis of Forgiving Data Extractors

Neural Survival Recommender

Random Semantic Tensor Ensemble for Scalable Knowledge Graph Link Prediction

The Influence of Early Respondents: Information Cascade Effects in Online Event Scheduling

Modeling Event Importance for Ranking Daily News Events

Concept Embedded Convolutional Semantic Model for Question Retrieval

Directed Edge Recommender System

S-HOT: Scalable High-Order Tucker Decomposition

Evolution of Ego-networks in Social Media with Link Recommendations

A Cost Model for Long-Term Compressed Data Retention

Summarizing Answers in Non-Factoid Community Question-Answering

Link Prediction with Cardinality Constraint

Multi-Column Convolutional Neural Networks with Causality-Attention for Why-Question Answering

Reliable Medical Diagnosis from Crowdsourcing: Discover Trustworthy Answers from Non-Experts

Content Provider	ACM Digital Library
Author	Du, Nan Li, Yaliang Li, Qi Fan, Wei Gao, Jing Liu, Chaochun Sun, Huan Xie, Yusheng
Abstract	Nowadays, increasingly more people are receiving medical diagnoses from healthcare-related question answering platforms as people can get diagnoses quickly and conveniently. However, such diagnoses from non-expert crowdsourcing users are noisy or even wrong due to the lack of medical domain knowledge, which can cause serious consequences. To unleash the power of crowdsourcing on healthcare question answering, it is important to identify trustworthy answers and filter out noisy ones from user-generated data. Truth discovery methods estimate user reliability degrees and infer trustworthy information simultaneously, and thus these methods can be adopted to discover trustworthy diagnoses from crowdsourced answers. However, existing truth discovery methods do not take into account the rich semantic meanings of the answers. In the light of this challenge, we propose a method to automatically capture the semantic meanings of answers, where answers are represented as real-valued vectors in the semantic space. To learn such vector representations from noisy user-generated data, we tightly combine the truth discovery and vector learning processes. In this way, the learned vector representations enable truth discovery method to model the semantic relations among answers, and the information trustworthiness inferred by truth discovery can help the procedure of vector representation learning. To demonstrate the effectiveness of the proposed method, we collect a large-scale real-world dataset that involves 219,527 medical diagnosis questions and 23,657 non-expert users. Experimental results show that the proposed method improves the accuracy of identified trustworthy answers due to the successful consideration of answers' semantic meanings. Further, we demonstrate the fast convergence and good scalability of the proposed method, which makes it practical for real-world applications.
Starting Page	253
Ending Page	261
Page Count	9
File Format	PDF
ISBN	9781450346757
DOI	10.1145/3018661.3018688
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-02-02
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Medical question answering Truth discovery Semantic meanings
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

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