Paper Info
Title
Extracting Precise Link Context Using NLP Parsing Technique
Abstract
Link context has been exploited extensively ever since the advent of the World Wide Web, but the approach to extracting precise link context has not been fully explored and many state-of-the-art extraction methods are based on simplistic heuristics and require ad-hoc parameters. In this paper, we propose a novel two-step extraction model, which aims to systematically derive link context of quality as high as anchor text. In the macroscopic analysis step, a systematic web page structure analysis is performed to locate the content cohesive text region and potential relevant header or header like tags. In the microscopic extraction step, an English parser is used to extract the relevant sentence fragments in the text region and the nearest heading text is encompassed if the need arises. Preliminary experimental results proved our approach's effectiveness.
Year
DOI
Venue
2004
10.1109/WI.2004.10164
Web Intelligence
Keywords
Field
DocType
link context,state-of-the-art extraction method,text region,derive link context,extracting precise link context,nlp parsing technique,novel two-step extraction model,microscopic extraction step,precise link context,macroscopic analysis step,content cohesive text region,anchor text,web pages,information retrieval,html,structure analysis,microscopy,context modeling,world wide web,data mining
Data mining,Web page,Computer science,Context model,Anchor text,Web modeling,Heuristics,Natural language processing,Artificial intelligence,Header,Information retrieval,Parsing,Sentence
Conference
ISBN
Citations 
PageRank 
0-7695-2100-2
2
0.40
References 
Authors
14
2
Name
Order
Citations
PageRank
Qingyang Xu1152.85
Wanli Zuo234242.73