The wealth of information generated by users interacting with the network and its applications is often under-utilized due to complications in accessing heterogeneous and dynamic data and retrieving relevant information from sources having possibly unknown formats and structures. Processing complex requests on such information sources can, thus, be costly, though not guaranteeing user satisfaction. Furthermore, dynamic contexts prevent substantial user involvement in the interpretation of the request. The paper envisions an innovative solution to process the above mentioned requests, limiting user involvement by exploiting information on: (a) user context (geo-location, interests, needs); (b) data and processing quality; (c) similar requests repeated over time. By interpreting a request in a novel way by means of a Wearable Query (WQ), i.e., a query that captures the user and request specificities, we envision a methodological and technological solution for WQs in the presence of repeated information needs in distributed, heterogeneous, dynamic environments, with emphasis on the geo-spatial dimension and on data quality.
A. Belussi, B. Catania, G. Guerrini, F. Mandreoli, R. Martoglia, W. Penzo (2013). Wearable Queries: Adapting Common Retrieval Needs to Data and Users. New York : ACM New York [10.1145/2524828.2524835].
Wearable Queries: Adapting Common Retrieval Needs to Data and Users
PENZO, WILMA
2013
Abstract
The wealth of information generated by users interacting with the network and its applications is often under-utilized due to complications in accessing heterogeneous and dynamic data and retrieving relevant information from sources having possibly unknown formats and structures. Processing complex requests on such information sources can, thus, be costly, though not guaranteeing user satisfaction. Furthermore, dynamic contexts prevent substantial user involvement in the interpretation of the request. The paper envisions an innovative solution to process the above mentioned requests, limiting user involvement by exploiting information on: (a) user context (geo-location, interests, needs); (b) data and processing quality; (c) similar requests repeated over time. By interpreting a request in a novel way by means of a Wearable Query (WQ), i.e., a query that captures the user and request specificities, we envision a methodological and technological solution for WQs in the presence of repeated information needs in distributed, heterogeneous, dynamic environments, with emphasis on the geo-spatial dimension and on data quality.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.