1. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU1 Semantic Information Access Atilla ELÇİ Dept. of Computer Engineering Eastern Mediterranean University

2. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU2 Semantic Info Access  Shortcomings of common-place Web and search technology  Applications of SemTech to knowledge access: Semantic search and browse tools Natural language generation Device independence.  Davies et al. Ch. 8.

3. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU3 Shortcomings of Current Web and Search Technology  Query construction: Syntactic units such as keywords/terms are used. Polysemy: multiple meanings Query ambiguity: # of keywords used per query (circa 2000): 2.2!  Lack of semantics: Inability to handle synonymy & polisemy Missed semantic links  Lack of context: Missing the context to disambiguate the user’s query.  Presentation of results: Often too many results  Managing heterogeneity: Providing a coherent view of diverse sources and types of information: very difficult and unsatisfactory at the best.  Lots of data but lacking information!  High recall but low precision!

4. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU4 Advantages of Semantic Web Technology  Resolving shortcomings of the current Web and search engines by: Exploiting machine-processable metadata Using ontological concepts to define queries Using semantic relations in defining queries Providing information not simply data  Future search engines must adapt to “information-centric” approach rather than document-centric one in order to seek: Relevant sections not simply documents Digest of info from several docs/sections

5. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU5 Semantic Search and Browse Tools  Searching the XML: QuizXML: XML-aware search; produces index map of keywords vs tags XSearch semantic search engine: provides semantically-relevant document fragments in response to a query (tags & keywords). XRANK XML search engine: query term is matched against document content & document markup. Extends Google Page Rank Algorithm.  Searching semantic data: RDF: QuizRDF: free-text search & RDF annotation search. Provides searching browsing.  Exploiting domain-specific knowledge: Rocha et al.’s Search Arch:  Spead activation: keyword-based document search, and  Using domain-specific semantic model Guha et al.’s ABS (activity-based search): people, places, events, news items. Combines searching conventşional search engine and enhancing findings through semantic knowledge base (RDF annotation) Popov et al.’s KIM (knowledge and information management) infrastructure, in order to enhance search:  Exploits ontological knowledge base  Provides automated semantic annotation method

6. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU6 Semantic Search and Browse Tools  Searching for Semantic Web resources: Swoogle Semantic Web Search Engine: to find ontologies and related instance data on the Web. Swoogle Semantic Web Search Engine Other ontology search engines? Mostly for RDF (instance data).  Wikipedia entry: Semantic Search “attempts to augment and improve traditional Research Searches by leveraging XML and RDF data from semantic networks to disambiguate semantic search queries and web text in order to increase relevancy of results.”Semantic SearchXMLRDFsemantic networks  Study Google’s search algorithm if you can find it.Google  Take a look at the Alexa Web Search Platform search engine.Alexa Web Search Platform  Take a look at WebCrawler.com paradigm: metasearch engine of search engines.WebCrawler.commetasearch engine  At last, a semantic search engine: See Hakia.com:Hakia.com A Turkish initiative but in the USA. Check Partners, one of them is KVK. Just raised another US$5 M totalling so far US$18 M.  Another one: PowerSet.PowerSet  Another recent one: AskMeNow.AskMeNow

7. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU7 Semantic Search & Browse Tools (cont’d)  Semantic Browsing: Magpie: plug-in that adds an ontology-based semantic layer onto the web pages as they are browsed. CS AKTiveSpace: web application for UK CS research domain. Haystack: a browser for semweb info agregating and visualizing RDF data from multiple arbitrary locations. W3C’s Annotea Project & AmayaAnnotea Project Amaya Yuce’s Site Insight. Yuce’s Site Insight

8. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU8 Natural Language Generation (NLG) from Ontologies Def.: taking structured data in a knowledge base as input and producing natural language text, tailored to the presentational context and the target reader.  Taxonomy / ontology verbalizers: Template-based or text-generator-based Takes advantage of tax/ont hierarchy, user history, and available semantic annotation in KB. Exs.: Wilcock’s general purpose verbalizer, Ontogeneration Project  Summarizers: Ontosum using RDF triples Miakt: domain- & ontology-specific Approach:  Verbalize based on discourse schema: active-action, passive- action, attribute, part-whole  Semantic agregation

9. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU9 Device Independence at Presentation Layer  Skim through Sect. 8.4

10. Advanced Semantic Querying  Leveraging the Expressivity of Grounded Conjunctive Query Languages Leveraging the Expressivity of Grounded Conjunctive Query Languages By Alissa Kaplunova, Ralf Möller and Michael WesselAlissa KaplunovaRalf MöllerMichael Wessel PDF (325.7 KB) 14/05/'07 upd 01/06/08CmpE 588 Spring 2008 EMU10

11. Conferences  ESWC-08 Workshop on Semantic Search : ESWC-08 Workshop on Semantic Search Workshop pf ESWC 2008, 1-5 June 2008, Tenerife, Spain. In recent years we have witnessed tremendous interest and substantial economic exploitation of search technologies. On the other hand semantic repositories and reasoning engines have advanced to a state where querying and processing of this knowledge can scale to realistic IR scenarios. As such, semantic technologies are now in a state to provide significant contributions to IR problems. This workshop intends to investigate the potential and the challenges of Semantic Search systems. Main topics of interest of the workshop cluster around the areas:  Tasks and Interaction Paradigms for Semantic Search,  Query Construction and Resource Modelling for Semantic Search,  Algorithms and Infrastructures for Semantic Search, and  Evaluation of Semantic Search. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU11

12. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU12 Commercial Conferences  Data Modeling Seminars and Workshops by Wilshire Conferences:Wilshire Conferences Designing and Building Ontologies: An ontology is a formal description of the meaning of the information stored in a system. It resembles a conceptual model, but goes much beyond a conceptual model in that the formal definitions allow the system to infer class membership based on properties. Additionally, inference engines, running on ontologies, allow users to extract and integrate information stored in distributed systems. This workshop, which will contain a number of live demos and student exercises, will cover practical issues in employing ontologies. A 4-DAY Seminar with Dave McComb and Simon Robe, $1795. Designing and Building Ontologies DAMA Symposium + Wilshire Meta-Data ConferenceWilshire Meta-Data Conference 2007 Semantic Technology Conference

13. 14/05/'07 upd 22/04/08CmpE 588 Spring 2008 EMU13 References  John Davies, Rudi Studer, Paul Warren (Editors): Semantic Web Technologies: Trends and Research in Ontology-based Systems, John Wiley & Sons (July 11, 2006). ISBN: 0470025964. Ch. 8.: pp. 139-169.  W3C Semantic Web Tools Wiki page:Semantic Web Tools Check Jena, SemWeb, Protégé, Swoop, etc.