1. What to do when one size does not fit all?! Arjen P. de Vries [email_address] Centrum Wiskunde & Informatica Delft University of Technology Spinque B.V.
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9. The one size fits all "semantically enhanced retrieval model“? BM25 BM25F LM RM VSM DFR QIR? Learning to rank? Document Collection: Anchors Entity types Sentiment Tweets Cited documents … Context User Ran ked list of answers
11. Parameterised Search System Cannot we ‘remove’ this IR engineer from the loop, like DBMS software removes the data engineer from the loop? Cornacchia, De Vries, ECIR 2007 A Parametrised Search System
38. 1. Which universities/colleges hold patents? 2. Who are the inventors named in those patents? 3. Which inventors are active in the area of our company? Real-life patent search example: Which researchers associated to universities and colleges should our Human Resources manager know to hire the right people on time?
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Editor's Notes
Viewing a BB as a function can be used later to sketch SpinQL.
Does “Entity-based ranking” make sense?
NOTE: MATERIALIZED VIEWs, where supported (not in MonetDB), can be used instead of TABLEs when stored relations (index) are expected to get updates.
This is how it should be done. How it is done at the moment: always append (like filters). Up/down means: upvote/downvote the selected bucket
This is how it should be done. How it is done at the moment: always append (like filters). Up/down means: upvote/downvote the selected bucket