Searching Linked Data with Spinque
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Spinque @ Search Engines Amsterdam (SEA) http://www.meetup.com/SEA-Search-Engines-Amsterdam/events/216345662/ Spinque is a spin-off company from CWI that builds on the research into Databases and Information Retrieval integration. We build tailor made search engines over connected datasets. With the Spinque technology we compose a search engine out of building blocks and compile this “search strategy” into an efficient query program. In the talk we explain and demonstrate the Search by Strategy approach. In addition, we discuss our current developments and challenges in searching Linked Data. Bio: Michiel Hildebrand received his PhD from University of Amsterdam (at CWI) in 2010 for his research on access to Linked Data. He worked as a researcher at VU University and CWI. In 2014 he joined Spinque to apply the company’s search by strategy approach to Linked Data.
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Searching Linked Data with Spinque
- 1. Searching Linked Data with Spinque Michiel Hildebrand, Wouter Alink, Roberto Cornacchia, Arjen de Vries Search Engines Amsterdam, January 30 2015
- 2. background concept product Information Retrieval and DB integration Cornacchia et al. Flexible and efficient IR using Array Databases. VLDB‘08 Journal Mühleisen et al. Column Stores as an IR Prototyping Tool. ECIR’14 & SIGIR’14 Search by Strategy Alink et al. Searching CLEF-IP by strategy. CLEF’09 PatOlympics, 2010 and 2011 Tailored access to connected datasets Koninklijke Bibliotheek, Wageningen Universiteit, Beeld&Geluid, Elsevier, Heineken, ...
- 3. Heterogenous Data Hang Li et al. A new approach to intranet search based on information extraction. CIKM’05 Complex information needs SQL CSV XML HTML OAI JSON
- 4. Heterogenous University Data Financial administration (ERP) Contract administration (CMS) Contract documents (CMS attachments) Publication database (Institutional Repository) Publication documents (Institutional Repository PDFs) Employee database (address lists, ERP+CMS) Companies (CMS + ERP + document mentions) Subsidy database (CMS) Departments (address lists, CMS) Web addresses (extracted from documents) Topic (assigned to publications) Research programmes (dependent on funding scheme) Complex information needs What funding schemes are the primary source of income? Can we move to Europe when Dutch funding dries up? Who has active relations with partner X? “Valorisation”; new national funding requirements What industry sectors do we depend upon? How many projects in smart cities? Green energy? Cloud computing? Etc. How are strategic decisions implemented? Has objective “move from Telecom toward ICT” been achieved, and how does it develop over time?
- 5. Heterogenous University Data Harvest and link data, model as a graph Complex information needs Search by Strategy
- 6. Project by topic Search in attachments of projects Search for project contracts (by metadata) Traverse from attachments to projects & combine results
- 7. Topic expert Search objects about topic Expand with neighbours in and out Return related persons Ranked by tf-idf on relations
- 8. Norbert Fuhr, Thomas Rölleke. A Probabilistic Relational Algebra for the Integration of Information Retrieval and Database Systems (1994)
- 9. API STRATEGY EDITOR COMPILERINDEXING PIPELINE SQL CSV HTML OAI XML APPLICATIONS
- 10. Search by Strategy (visual) modelling of search processes Rank. Everything. Always. all-round probabilistic search Many strategies, one data model many search engines, one index
- 11. Components Supporting the Open Data Exploitation
- 12. API SQL CSV HTML OAI XML STRATEGY EDITOR COMPILER APPLICATIONSINDEXING PIPELINE
- 14. Application front-end 400 lines of Javascript
- 15. autocompletion Application back-end 3 search strategies location search location + text search
- 16. API Builder for Open Data? Supporting (search) application developers Gregory Grefenstette. Search-based applications. 2010 Jamie Callan. Search Engine Support For Software Applications. CIKM 2010 Keynote Who builds search strategies? Developers are not IR specialists Domain specialists neither How to handle schema-mess? in a heterogeneous dataspace
- 18. Happy alignments are all alike, every unhappy alignment is unhappy in it’s own way Jacco van Ossenbruggen 2012 (improvisation on Anna Karenina, Leo Tolstoy 1887)
- 19. Alignment strategies Interactive vocabulary alignment, Jacco van Ossenbruggen, Michiel Hildebrand, Victor de Boer, TPDL 2011 Coming soon Spinque Alignment Service Beeld&Geluid, Naturalis, Rijksdienst Cultureel Erfgoed (RCE)
Editor's Notes
- First part: history of Spinque and overview of Spinque technology Second part: apply Spinque technology to search Linked Data
- Background: Spinque started as a spinoff company from CWI. Research on Information Retrieval on top of Databases. People not familiar with this work, one of the interesting advantages as that it creates a flexible environment where you can intuitively combine keyword search with structured queries. Implement XML search, Graph search, Feature-based search??? This flexibility is one of the key features from Spinque. Concept: Spinque started in the context of a project to search patents. Finding patents is a complex task performed by domain specialists. Patents are structured documents and linked to references and external documents. Specialists know how to search in which parts. Spinque provided the environment to express complex search “strategy”. Not as a query, but as the algorithm. Spinque won the PatOlympics twice, 2010, 2011. Evolved into a technology and toolset to make connected data accessible. Commercial and research projects to build search engines for ...
- An example with data from a University. Universities have many datasources. In various data formats: XML files, CSV files from a database dump. APIs. Crawl data from the Web. They have information needs that span over these sources
- An example with data from a University. Universities have many datasources. In various data formats: XML files, CSV files from a database dump. APIs. Crawl data from the Web. They have information needs that span over these sources
- An example with data from a University. Universities have many datasources. In various data formats: XML files, CSV files from a database dump. APIs. Crawl data from the Web. They have information needs that span over these sources
- The project COMSODE is an SME-driven RTD project aimed at progressing the capabilities in the field of Open Data re-use. Our concept is an answer to barriers still present in this young area: data published by various Open Data catalogues are poorly integrated; quality assessment and cleansing are seldom addressed. Costs of Open Data consumption are high and Open Data usage is still poor. COMSODE tries to change the game.
- Towards the Future
- One more future topic. Links between datasets are not always there?
- First part: history of Spinque and overview of Spinque technology Second part: apply Spinque technology to search Linked Data