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KE4IR: Knowledge Extraction for Information Retrieval
Published on Jul 28, 20161735 Views
Document retrieval is the task of returning relevant textual resources for a given user query. In this paper, we investigate whether the semantic analysis of the query and the documents, obtained expl
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Chapter list
KE4IR: Knowledge Extraction for Information Retrieval00:00
Main Message00:20
Outline00:41
Document Retrieval01:02
Motivation01:21
KE4IR In a nutshell02:31
Mentions & Semantic Terms03:33
Semantic Layers - 1. URI (aka “entities”)04:22
Semantic Layers - 2. TYPES05:07
Semantic Layers - 3. FRAME06:10
Semantic Layers - 4. TIME07:36
Summing Up08:46
Retrieval Model09:34
Building the vectors10:26
Building the vectors: example11:00
Implementation11:23
PIKES In a nutshell12:12
Main Characteristics13:27
Summary - 114:47
Summary - 215:06
Summary - 315:18
Summary - 415:22
Evaluation Setup - 115:28
Summary - 216:33
Evaluation Results: Comparison with the baselines17:32
Evaluation Results: Impact of various layer combinations19:12
Evaluation Results: Query-by-query analysis19:50
Balancing Textual vs Semantic Content21:06
Evaluation Material22:31
Conclusions22:42