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Browse Prior Art Database

Collaborative active reading

IP.com Disclosure Number: IPCOM000238179D
Publication Date: 2014-Aug-07
Document File: 5 page(s) / 96K

Publishing Venue

The IP.com Prior Art Database

Abstract

The invention is a novel method and apparatus to automatically provide to readers interesting and useful sections of text along with associated quality annotations from other readers. It enhances the effectiveness and efficiency of reading, and improves the users’ reading and learning experience. This disclosure provides a context sensitive method for analyzing the readers’ annotation and rating data, by integrating the topic/term-wise comment/reviewing driven graph to generate a list of outputs for further applcaitions.

This text was extracted from a PDF file.
This is the abbreviated version, containing approximately 65% of the total text.

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Collaborative active reading

The invention is a novel method and apparatus to automatically provide to readers interesting and useful sections of text along with associated quality annotations from other readers. It enhances the effectiveness and efficiency of reading, and improves the users' reading and learning experience. Automatic identification/recommendation of highlighted sections; Automatic repopulation of annotations associated with the key word, key sections; Repopulation of tags and annotations to new books by correlating the book contents (cold-start problem).


A system for collecting and analyzing the reader's reading behavior

- Collect the readers' behavior like highlight, underline, tag, note, annotation, comments etc and the associated term/key word/paraphrase/sentence/sections


- Collect the readers' rating against each other's comments/annotations etc


A method for analyzing the readers' annotation & rating data, and generate


- authorized annotation recommend list for reading


- hot term/key word/paraphrase/sentence/sections for a given article

- Model each reader as a node associated with the attributes using one's profile information like membership, profession etc.


- Model the rating between readers as the directed edges

- Build a graph using the aforementioned nodes and edges and using graph analysis techniques to find out the authority readers and their annotations.

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A work flow is shown as follows:

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1) For each ter...