Abstract:
This paper presents an incremental, inductive learning approach to query-by-examples for information retrieval (IR) and database management systems (DBMS). After briefly reviewing conventional information retrieval techniques and the prevailing database query paradigms, we introduce the ID5R algorithm, previously developed by Utgoff, for `intelligent' and system-supported query processing.
Abstract:
Identity resolution is central to fighting against crime and terrorist activities in various ways. Current information systems and technologies deployed in law enforcement agencies are neither adequate nor effective for identity resolution. In this research we conducted a case study in a local police department on problems that produce difficulties in retrieving identity information. We found that more than half (55.5%) of the suspects had either a deceptive or an erroneous counterpart existing in the police system. About 30% of the suspects had used a false identity (i.e., intentional deception), while 42% had records alike due to various types of unintentional errors. We built a taxonomy of identity problems based on our findings. © Springer-Verlag Berlin Heidelberg 2005.
Abstract:
To mine the rich social media data produced in virtual worlds, an integrated framework combines bot- and spider-based approaches to collect avatar behavioral and profile data. © 2010 IEEE.
Abstract:
The Department of Homeland Security monitors vehicles entering and leaving the country at land ports of entry. Some vehicles are targeted to search for drugs and other contraband. Customs and Border Protection agents believe that vehicles involved in illegal activity operate in groups. If the criminal links of one vehicle are known then their border crossing patterns can be used to identify other partner vehicles. We perform this association analysis by using mutual information (MI) to identify pairs of vehicles that are potentially involved in criminal activity. Domain experts also suggest that criminal vehicles may cross at certain times of the day to evade inspection. We propose to modify the mutual information formulation to include this heuristic by using cross-jurisdictional criminal data from border-area jurisdictions. We find that the modified MI with time heuristics performs better than classical MI in identifying potentially criminal vehicles. © Springer-Verlag Berlin Heidelberg 2006.
