Recently, there has been a significant amount of interest in automatically creating large-scale knowledge bases from unstructured text. Compared to traditional, manually created representations, these knowledge bases have the advantage of scale and coverage. They often contain tens of millions of propositions, represented using a variety of encodings, from simple binary assertions to more complicated frame-like structures, and are extracted by parsing and analyzing large Web corpora.
This special issue seeks theories, algorithms and applications of automatically extracted Web-scale knowledge. Example topics include:
IJSWIS is one of the top journals in WWW based most recent 5 year data on Microsoft Academic Search and has over 7 citations/publication (accessed Dec. 1, 2011). It is included in most major indices including CSI, with Thomson Scientific impact factor 2.345. . We seek high quality manuscripts suitable for an archival journal based on original research. If the manuscript is based on a prior workshop or conference submission, submissions should reflect significant novel contribution/extension in conceptual terms and/or scale of implementation and evaluation (authors are highly encouraged to clarify new contributions in a cover letter or within the submission).
Submissions should ideally be around 8,000 words (max. 10,000 words without Guest Editor's prior consent) in length. Accepted paper will be asked to formatted manuscripts according to the publisher's guidelines at: http://www.igi-global.com/journals/guidelines-for-submission.aspx
Check this space in January for manuscript submission instructions.