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From Queriability to Informativity, Assessing “Quality in Use” of DBpedia and YAGO
Published on Jul 28, 20162054 Views
In recent years, an increasing number of semantic data sources have been published on the web. These sources are further interlinked to form the Linking Open Data (LOD) cloud. To make full use of thes
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Chapter list
From Queriability to Informativity, Assessing "Quality in Use" of DBpedia and YAGO00:00
What is data quality?00:14
Metrics on LOD00:41
Quality model in software engineering00:57
Data quality model we proposed01:18
The most common usage scenario in data sets - Query and Check the Answer01:45
``Quality in use’’ are based on ``Context of use”02:18
Outline - 102:48
Manual process to query on datasets02:50
Summarized Processes of constructing a query03:22
Vocabularies finding steps03:46
Queriability Metrics04:15
Informativity Metrics04:37
Outline - 204:52
Evaluated Knowledge Bases04:57
Questions05:05
Classify questions into different Patterns05:22
Evaluation process05:57
1. Select question and KB06:21
2. Set the domain06:37
3. Set property constraint07:28
4. Generate query08:09
Outline - 308:25
Untitled08:28
Query Construction on Domain08:38
Query Construction Time on Property Constraint09:13
Number of Attempts in DBpedia is more than that in YAGO09:43
Even with the help of our tool, it is not easy to construct a query for any question09:43
DBpedia has a rather low precision10:00
DBpedia and YAGO have low recalls10:48
In summary11:15
Lessons learned11:35
Big questions12:14
Thank you12:15