Hamid Haidarian Shahri

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Configuration management is an important problem in large software systems. When dealing with hundreds of components, keeping track of version changes and various dependency constraints imposed on the system, throughout its development life cycle is very challenging. Current approaches are ad hoc and proprietary, and there exists no standard for specifying(More)
What commonsense knowledge do intelligent systems need, in order to recover from failures or deal with unexpected situations? It is impractical to represent predetermined solutions to deal with every unanticipated situation or provide predetermined fixes for all the different ways in which systems may fail. We contend that intelligent systems require only a(More)
Sensor networks have shown tremendous growth in many domains such as environmental monitoring. The data captured from the physical world through these sensor devices, however, tend to be incomplete, noisy, and unreliable. Traditional data cleaning techniques cannot be applied to such data as they do not take into account the strong spatial and temporal(More)
Data cleaning deals with the detection and removal of errors and inconsistencies in data, gathered from distributed sources. This process is essential for drawing correct conclusions from data in decision support systems. Eliminating fuzzy duplicate records is a fundamental part of the data cleaning process. The vagueness and uncertainty involved in(More)
Data cleaning is an inevitable problem when integrating data from distributed operational databases, because no unified set of standards spans all the distributed sources. One of the most challenging phases of data cleaning is removing fuzzy duplicate records. Approximate or fuzzy duplicates pertain to two or more tuples that describe the same real-world(More)
Vehicle tracking has a wide variety of applications from law enforcement to traffic planning and public safety. However, the image resolution of the videos available from most traffic camera systems, make it difficult to track vehicles based on unique identifiers like license plates. In many cases, vehicles with similar attributes are indistinguishable from(More)
In this paper, when we use the term ontology, we are primarily referring to linked data in the form of RDF(S). The problem of ontology mapping has attracted considerable attention over the last few years, as the deployment of ontologies is increasing with the advent of the Web of Data. We identify two sharply distinct goals for ontology mapping, based on(More)
Currently, our interactions with devices are constrained, as we need to program/configure devices, primarily through some artificial interface, instead of interacting through a dialog agent. This limitation in human-device interactions is a major obstacle to the integration of devices (e.g. PDA, GPS) in our daily activities. Considering the numerous(More)
The problem of ontology mapping has attracted considerable attention over the last few years, as the usage of ontologies is increasing. In this paper, we revisit the fundamental assumptions that drive the mapping process. Based on real-world use cases, we identify two distinct goals for mapping, which are: (i) ontology development and (ii) facilitating(More)