The Semantic Puzzle

Andreas Blumauer

Introducing SKOSsy – generate thesauri on the fly!

Imagine you could generate any thesaurusA thesaurus is a book that lists words grouped together according to similarity of meaning, in contrast to a dictionary, which contains definitions and pronunciations. The largest thesaurus in the world is the Historical Thesaurus of the Oxford English Dictionary, which contains more than ... you would like for nearly any knowledge domain you can think of with quite a good quality! Sounds impossible? Reminds you of all the promises made by text miningText mining, sometimes alternately referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the divining of patterns and trends through means such as ... software which generates “semantic nets” from scratch?

Let me introduce you to SKOSsy. I will explain what this web service can do for you:

SKOSsy generates SKOSSimple Knowledge Organization System (SKOS) is a family of formal languages designed for representation of thesauri, classification schemes, taxonomies, subject-heading systems, or any other type of structured controlled vocabulary. SKOS is built upon RDF and RDFS, and its main objective is to ... based thesauri in German or in English for a domain you are interested in. Not any domain but nearly any: SKOSsy extracts data from DBpediaDBpedia is a project aiming to extract structured information from the information created as part of the Wikipedia project. This structured information is then made available on the World Wide Web. DBpedia allows users to query relationships and properties associated with Wikipedia resources, ..., so it can cover anything which is in DBpedia. Thus, SKOSsy works well whenever a first seed thesaurus should be generated for a certain organisation or project. If you load the automatically generated thesaurus into an editor like PoolParty Thesaurus Manager (PPT) you can start to enrich the knowledge model by additional concepts, relations and links to other LODLinked Open Data (LOD) stands for freely available data on the World Wide Web, which can be identified via Uniform Resource Identifier (URI) and can be accessed and retrieved directly via HTTP. Finally link your data to other data to provide context. sources. But you don´t have to start in the open countryside with your thesaurus project.

Let me give you an example: Imagine you are working for a company which is an international plant builder and you would like to index several thousands of documents the “semantic way”. You have to walk through the following steps:

  1. Identify proper categories in Wikipedia/DBpedia which describe best what your business or your domain is all about. Those categories should contain pages / resources which are related to the documents you would like to index. For example: or
  2. After you have selected proper categories SKOSsy will traverse DBpedia for you and collect all resources, their hierarchical and non-hierarchical relations, alternative labels, definitions and other properties and put them together as a valid SKOS thesaurus; this step will last a couple of minutes. (Find the resulting vocabulary here)
  3. Load the resulting thesaurus into PPT, explore it, improve it and enrich it with additional facts.
  4. After you´re done you can generate a tailor-made text extractor by using PoolParty Extractor (PPX) which is the second component of PoolPartyWeb based ontology manager which can serve as a central hub for your knowledge organization. With PoolParty you can organize and maintain knowledge models based on widely accepted specifications like RDF, SPARQL and SKOS. product family
  5. With PPX and its extraction model especially curated for your special use case you can extract named entities from your documents automatically and index your documents in a meaningful way.
  6. After a few seconds your semantic search engine is ready to be used. PoolParty Semantic Search (PPS) which is the third PoolParty component will offer some nice facilities like categorized auto-complete, faceted search, content recommendation (similarity search) and smart search suggestions to ease your life as a knowledge worker.

We have constantly discussed the application of thesauri and other knowledge models to improve search over the last years. Many people understood straight away why thesaurus based search is most often much better than search algorithms purely based on statistics. Of course the big contra always was, “the costs are too high to establish a “good-enough” thesaurus or even a “high-quality” one”.

With SKOSsy in place those kinds of arguments become weaker and weaker. To sum up,

  • SKOSsy makes heavy use of Linked Data sources, especially DBpedia
  • SKOSsy can generate SKOS thesauri for virtually any domain within a few minutes
  • Such thesauri can be improved, curated and extended to one´s individual needs but they serve usually as “good-enough” knowledge models for any semantic search application you like
  • SKOSsy based semantic search usually outperform search algorithms based on statistics since they contain high-quality information about relations, labels and disambiguation
  • SKOSsy works perfectly together with PoolParty product family

If you are interested in the results produced by SKOSsy, just send us a short note about your domain or your project and we will send you an invitation as beta-tester or prepare a demo for you.

Enhanced by Zemanta