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Understanding User Intents in Online Health Forums
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Understanding User Intents in Online Health Forums

Category : Data Mining


Sub Category : JAVA


Project Code : ITJDM10


Project Abstract

UNDERSTANDING USER INTENTS IN ONLINE HEALTH FORUMS

ABSTRACT

                  Online health forums provide a convenient way for patients to obtain medical information and connect with physicians and peers outside of clinical settings. We derive a taxonomy of intents to capture user information needs in online health forums, and propose novel pattern based features for use with a multiclass support vector machine (SVM) classifier to classify original thread posts According to their underlying intents. Since no dataset existed for this task, we employ three annotators to manually label a dataset of  HealthBoards posts spanning four forum topics. Experimental results show that a SVM using pattern based features is highly capable of identifying user intents in forum posts, reaching a maximum precision of 75%, and that a SVM-based hierarchical classifier using both pattern and word features outperforms its SVM counterpart that uses only word features. Furthermore, comparable classification performance can be achieved by training and testing on posts from different forum topics.

 

EXISTING SYSTEM

PROPOSED SYSTEM

EXISTING CONCEPT:-

Existing forums provide a convenient way for patients to obtain medical information and connect with physicians and peers outside of clinical settings.

Large quantities of unstructured and diversified content generated on these forums.

PROPOSED CONCEPT:-

We derive a taxonomy of intents to capture user information needs in online health forums, and propose novel pattern based features for use with a multiclass support vector machine (SVM) classifier to classify original thread posts according to their underlying intents.

Since no dataset existed for this task, we employ three annotators to manually label a dataset of 1,192 Health Boards posts spanning four forum topics.

EXISTING ALGORITHM:-

Greedy algorithm

PROPOSED ALGORITHM:-      

Novel pattern.

ALGORITHM DEFINITION:-

 A greedy algorithm is an algorithm that follows the problem solving heuristic of making the locally optimal choice at each stage with the hope of finding a global optimum.

ALGORITHM DEFINITION:-

Subjective understanding of user intents has also been extensively studied in the context of general Community Question Answering (CQA) services.

DRAWBACKS:-

Large quantities of unstructured and diversified content generated on these forums make it difficult for users to digest and extract useful information.

Understanding user intents would enable forums to find and recommend relevant information to users by filtering out threads that do not match particular intents.

ADVANTAGES:-

Results show that a SVM using pattern based features is highly capable of identifying user intents in forum posts, reaching a maximum precision of 75%.

And that a SVM-based hierarchical classifier using both pattern and word features outperforms its SVM counterpart that uses only word features.

 
 
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