Intelligent Retrieval and Clustering of Inventions
Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Ericsson’s Region IPR & Licensing (RIPL) receives about 3000 thousands Invention Disclosures (IvDs) every year submitted by researchers as a result of their R&D activities. To decide whether an IvD has a good business value and a patent application should be filed; a rigorous evaluation process is carried out by a selected Patent Attorney (PA). One of most important elements of the evaluation process is to find prior art similar, including similar IvDs that have been evaluated before. These documents are not public and therefore can’t be searched using available search tools. For now the process of finding prior art is done manually (without the help of any search tools) and takes up significant amount of time.
The aim of this Master’s thesis is to develop and test an information retrieval search engine as a proof of concept to find similar Invention Disclosure documents and related patent applications. For this purpose, a SOLR database server is setup with up to seven thousand five hundred (7500) IvDs indexed. A similarity algorithm is implemented which is customized to weight different fields. LUCENE is then used to query the server and display the relevant documents in a web application.
Place, publisher, year, edition, pages
2015. , 70 p.
Information Retrieval, Solr, Lucene, Patents, Patent Search Engine, NoSql.
Computer and Information Science
IdentifiersURN: urn:nbn:se:kth:diva-187018OAI: oai:DiVA.org:kth-187018DiVA: diva2:928553