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Windows Azure Storage (WAS) is a cloud storage system that provides customers the ability to store seemingly limitless amounts of data for any duration of time. WAS customers have access to their data from anywhere at any time and only pay for what they use and store. In WAS, data is stored durably using both local and geographic replication to facilitate(More)
Incompleteness due to missing attribute values (aka " null values ") is very common in autonomous web databases, on which user accesses are usually supported through mediators. Traditional query processing techniques that focus on the strict soundness of answer tuples often ignore tuples with critical missing attributes, even if they wind up being relevant(More)
Incompleteness due to missing attribute values (aka " null values ") is very common in autonomous web databases, on which user accesses are usually supported through mediators. Traditional query processing techniques that focus on the strict soundness of answer tuples often ignore tuples with critical missing attributes, even if they wind up being relevant(More)
As more and more information from autonomous databases becomes available to lay users, query processing over these databases must adapt to deal with the imprecise nature of user queries as well as incompleteness in the data due to missing attribute values (aka " null values "). In such scenarios, the query processor begins to acquire the role of a(More)
In an environment of distributed text collections, the first step in the information retrieval process is to identify which of all available collections are more relevant to a given query and should thus be accessed to answer the query. Collection selection is difficult due to the varying relevance of sources as well as the overlap between these sources.(More)
Incompleteness due to missing attribute values (aka "null values") is very common in autonomous Web databases, on which user accesses are usually supported through mediators. Traditional query processing techniques that focus on the strict soundness of answer tuples often ignore tuples with critical missing attributes, even if they wind up being relevant to(More)
As more and more information from autonomous web databases becomes available to lay users, query processing over these databases must adapt to deal with the imprecise nature of user queries as well as incompleteness due to missing attribute values (aka " null values ") in the database. In such scenarios, the query processor begins to acquire the role of a(More)
Most data integration systems focus on " data aggregation " applications, where individual data sources all export fragments of a single relation. Given a query, the primary query processing objective is to select the appropriate subset of sources to optimize conflicting user preferences. We develop an adaptive data aggregation framework to effectively(More)
In an environment of distributed text collections, the first step in the information retrieval process is to identify which of all available collections are more relevant to a given query and should thus be accessed to answer the query. Collection selection is difficult due to the varying relevance of sources as well as the overlap between these sources.(More)