Lightweight Semantics over Web Information Systems Content Employing Knowledge Tags

A model of web information system content is crucial for its effective manipulation. We employ knowledge tags --- metadata that describe an aspect of an information artifact for purpose of the modeling. Knowledge tags provide a lightweight semantics over the content, which serves web information systems also for sharing knowledge about the content and interconnections between information artifacts. Knowledge tags represent not only content based metadata, but also a collaboration metadata, e.g. aggregations of an implicit user feedback including interactions with the content. To allow this type of metadata we should provide means for knowledge tags repository providing flexible and fast access for effective reasoning. In this paper we address issues related to knowledge tags repository and its automatic maintenance. Main design issues are based on considering dynamic character of the web of information artifacts, which results in content changes in time that can invalidate knowledge tags. We realized the web-scale repository via the MongoDB database. Proposed repository stores knowledge tags in Open Annotation model and supports inference via distributed SPARQL query processing algorithm for MapReduce.

[1]  Eric Prud'hommeaux,et al.  Annotea: an open RDF infrastructure for shared Web annotations , 2002, Comput. Networks.

[2]  Beryl Plimmer,et al.  iAnnotate: Exploring Multi-User Ink Annotation in Web Browsers , 2010, AUIC.

[3]  Jane Hunter,et al.  High Speed Capture, Retrieval and Rendering of Segment-Based Annotations on 3D Museum Objects , 2011, ICADL.

[4]  Robert Wilensky,et al.  Robust intra-document locations , 2000, Comput. Networks.

[5]  Jane Hunter,et al.  The Role of Digital Libraries in a Time of Global Change, 12th International Conference on Asia-Pacific Digital Libraries, ICADL 2010, Gold Coast, Australia, June 21-25, 2010. Proceedings , 2010, ICADL.

[6]  Herbert Van de Sompel,et al.  Memento: Time Travel for the Web , 2009, ArXiv.

[7]  Sang-goo Lee,et al.  SPARQL basic graph pattern processing with iterative MapReduce , 2010, MDAC '10.

[8]  Kurt Rohloff,et al.  An Evaluation of Triple-Store Technologies for Large Data Stores , 2007, OTM Workshops.

[9]  Zahir Tari,et al.  On the Move to Meaningful Internet Systems. OTM 2018 Conferences , 2018, Lecture Notes in Computer Science.

[10]  Pavol Bielik,et al.  Automated Acquisition of Domain Model for Adaptive Collaborative Web-Based Learning , 2012 .

[11]  Beryl Plimmer,et al.  RCA: experiences with an IDE annotation tool , 2006, CHINZ '06.

[12]  Zahir Tari,et al.  On The Move to Meaningful Internet Systems 2003: OTM 2003 Workshops , 2003, Lecture Notes in Computer Science.

[13]  Mária Bieliková,et al.  Lightweight semantics for the "wild Web" , 2011 .

[14]  HyeongSik Kim,et al.  From SPARQL to MapReduce: The Journey Using a Nested TripleGroup Algebra , 2011, Proc. VLDB Endow..

[15]  Sanjay Ghemawat,et al.  MapReduce: Simplified Data Processing on Large Clusters , 2004, OSDI.

[16]  Jane Hunter,et al.  A Collaborative Scholarly Annotation System for Dynamic Web Documents - A Literary Case Study , 2010, ICADL.

[17]  Shashank Tiwari,et al.  Professional NoSQL , 2011 .

[18]  Eduard Kuric.  Automatic Photo Annotation Based on Visual Content Analysis , 2011 .

[19]  Herbert Van de Sompel,et al.  Making web annotations persistent over time , 2010, JCDL '10.

[20]  Zahir Tari,et al.  On the Move to Meaningful Internet Systems 2005: CoopIS, DOA, and ODBASE, OTM Confederated International Conferences CoopIS, DOA, and ODBASE 2005, Agia Napa, Cyprus, October 31 - November 4, 2005, Proceedings, Part I , 2005, OTM Conferences.