Ranking with pre-trained language models (PLMs) has shown to be highly effective for
various Information Retrieval tasks. Previous studies investigated the performance of these …

Patent documents are important intellectual resources of protecting interests of individuals,
organizations and companies. Different from general web documents, patent documents …

We investigate the effect of feature weighting on document clustering, including a novel
investigation of Okapi BM25 feature weighting. Using eight document datasets and 17 well …

Prior-art search is an important task in patent retrieval. The success of this task relies upon
the selection of relevant search queries. Typically terms for prior-art queries are extracted …

The present invention provides a method and system for re-ranking search results in a
patent retrieval system where the query text is derived in whole or in part from a patent claim …

Patent prior art search is a type of search in the patent domain where documents are
searched for that describe the work previously carried out related to a patent application …

A Web archive usually contains multiple versions of documents crawled from the Web at
different points in time. One possible way for users to access a Web archive is through full …

Pseudo-relevance feedback (PRF) can enhance average retrieval effectiveness over a
sufficiently large number of queries. However, PRF often introduces a drift into the original …

Much computer vision research has focused on natural images, but technical documents
typically consist of abstract images, such as charts, drawings, diagrams, and schematics …

Retrievability provides an alternative way to assess an Information Retrieval (IR) system by
measuring how easily documents can be retrieved. Retrievability can also be used to …