NDLI: Enriching the web by modeling reading difficulty

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Computational frameworks for semantic analysis and wikification: keynote abstract

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Enriching the web by modeling reading difficulty

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Search using semantic framenet frames as variables

Learning user's intent using user tags: intelligent interactive image search system

Course specific search engines: a study in incorporating context into search

Named entity extraction and disambiguation: the missing link

Thoughts on the complex relation between linked data, semantic annotations, and ontologies

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Enriching the web by modeling reading difficulty

Content Provider	ACM Digital Library
Author	Collins-Thompson, Kevyn
Abstract	The ability to read and understand a text would seem to be a basic aspect of interacting with a rich information source like the Web, yet little is currently known about the nature of the Web, its users, and how users interact with content when seen through the lens of reading difficulty. For example, a document isn't relevant to a person's information need - at least, not immediately - if they can't understand it, yet Web search engines have traditionally ignored the problem of finding or providing content at the right level of difficulty as an aspect of relevance. I'll give an overview of recent research that shows how computing and applying metadata based on text readability at Web scale opens up new and sometimes surprising possibilities for enriching our interactions with the Web: from personalizing Web search results, to predicting user and site expertise, to estimating searcher motivation. I'll also highlight future challenges and opportunities in improving text readability analysis, particularly in light of the rapidly growing interest in large-scale applications for online education.
Starting Page	3
Ending Page	4
Page Count	2
File Format	PDF
ISBN	9781450324137
DOI	10.1145/2513204.2513206
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2013-10-28
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Reading difficulty Expertise modeling Semantic representation Web search Web interaction
Content Type	Text
Resource Type	Article

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