Paper Info
Title
Retrieval of Structured and Unstructured Data with vitrivr
Abstract
With the increase in sensory capability of mobile devices, the data that can be generated and used in a lifelogging context gets increasingly diverse. Such data is special in the context of multimedia, not only because of its close personal relationship with its originator, but also because of its diverse multimodality and its composition from structured, semi-structured, and unstructured data. This diversity poses retrieval challenges that are unique to lifelog data but which also have implications for retrieval activity in other multimedia domains. In this paper, we present the extensions made to the vitrivr open-source multimedia retrieval stack, in order to address some of these unique lifelogging challenges. For the participation to the 2019 Lifelog Search Challenge (LSC), we have extended vitrivr with the capability to process Boolean query expressions alongside content-based query descriptions in order to leverage the structural diversity inherent to lifelog data.
Year
DOI
Venue
2019
10.1145/3326460.3329160
ICMR '19: International Conference on Multimedia Retrieval Ottawa ON Canada June, 2019
Keywords
Field
DocType
Content-based Retrieval,Multimedia Retrieval,Lifelogging,Lifelog earch Challenge
Information retrieval,Computer science,Unstructured data,Artificial intelligence,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4503-6781-3
0
0.34
References 
Authors
0
5
Name
Order
Citations
PageRank
Luca Rossetto19221.00
Ralph Gasser266.95
Silvan Heller375.74
Mahnaz Amiri Parian402.03
H. Schuldt59820.60