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ContentSuggest

ContentSuggest
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Details Group Tabs

Details

During development and maintenance of a software product, software developers often search for relevant information in the web about an encountered error or exception, where they manually check the web pages returned by a search engine in order to extract a working solution. Both manual checking of the page content against the exception (and its context) and extracting an appropriate solution are non-trivial tasks. They are even more complicated with the bulk of noisy (e.g., advertisements, navigation menus) and irrelevant content in the web page. In this paper, we propose an IDE-based context-aware page content recommendation approach that not only returns all the noise-free (i.e., main) sections of a web page but also identifies the relevant sections of the page. The approach exploits the encountered exception and its context in the IDE in order to recommend the relevant sections of the webpage resulted from an IDE-based web search.

Categories:
  • Search,
  • Tools
Tags:
  • Context-relevant recommendation
Additional Details
Organization Name: 
University of Saskatchewan
Date Created: 
Wed, 2014-05-14 19:09
Date Updated: 
Thu, 2014-05-15 16:57
Submitted by: 
Masud Rahman
Metrics
DateRankingInstallsClickthroughs
March 2023NA0 (0%)7
February 2023NA0 (0%)14
January 2023NA0 (0%)11
December 2022NA0 (0%)14
November 2022NA0 (0%)11
October 2022NA0 (0%)22
September 2022NA0 (0%)10
August 2022NA0 (0%)9
July 2022NA0 (0%)17
June 2022NA0 (0%)8
May 2022NA0 (0%)15
April 2022NA0 (0%)11
View Data for all Listings
Errors

Unsuccessful Installs in the last 7 Days: 0

Download last 500 errors (CSV)
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