Pre-Grant Publication Number: 20100241416
View Prior Art submitted by the community. You can see full text, rate and annotate the Prior Art by clicking on
any of the listed Prior Art references. You can also click on the name of the person who submitted art to view their profile
and any other Prior Art they have previously submitted.
How to Rate Prior Art
Rating Prior Art - Click the thumbs up or down to indicate if a submission is relevant enough to the claims of the application to deserve a spot in the Top 10 submissions that will be forwarded to the patent examiner. Rating should be based only on relevance. For an explanation of prior art, please visit the Tutorial Page.
Rating Prior Art - Click the thumbs up or down to indicate if a submission is relevant enough to the claims of the application to deserve a spot in the Top 10 submissions that will be forwarded to the patent examiner. Rating should be based only on relevance. For an explanation of prior art, please visit the Tutorial Page.
Prior Art (2)
Title A comparative study on compositional translation estimation using a domain/topic-specific corpus col
ISBN
Description
This paper studies issues related to compiling bilingual lexicon for technical terms. In estimating bilingual term correspondences of technical terms, it is usually difficult to find an existing corpus for the domain of such technical terms. The authors adopt an approach of collecting a corpus for the domain of such technical terms from the Web. As a method of translation estimation for technical terms, they employ a compositional translation estimation technique.
Title Automatic information extraction from semi-structured Web pages by pattern discovery
ISBN
Description
This paper proposes a pattern discovery approach to the rapid generation of information extractors that can extract structured data from semi-structured Web documents. The authors introduce IEPAD (i.e., Information Extraction based on PAttern Discovery), which is a system that discovers extraction patterns from Web pages without user-labeled examples. IEPAD applies several pattern discovery techniques, including PAT-trees, multiple string alignments and pattern matching algorithms. Extractors generated by IEPAD can be generalized over unseen pages from the same Web data source.
0 days left
