PICASSO : exploratory search of connected subgraph substructures in graph databases
Recently, exploratory search has received much attention in information retrieval and database fields. This search paradigm assists users who do not have a clear search intent and are unfamiliar with the underlying data space. Specifically , query formulation evolves iteratively as the user becomes...
| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2019
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/105716 http://hdl.handle.net/10220/49545 http://www.vldb.org/pvldb/vol10/p1861-bhowmick.pdf |
| Summary: | Recently, exploratory search has received much attention in information retrieval and database fields. This search paradigm assists users who do not have a clear search intent and are unfamiliar with the underlying data space. Specifically , query formulation evolves iteratively as the user becomes more familiar with the content. Despite its growing importance, exploratory search on graph-structured data has received little attention in the literature. We demonstrate a system called picasso to realize exploratory sub-structure search on a graph database containing a set of small or medium-sized data graphs. picasso embodies several novel features such as progressive (i.e., iterative) formulation of queries visually and incremental processing, multi-stream results exploration wall to visualize, explore, and analyze search results to identify possible search directions. |
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