Efficient storage and domain-specific information discovery on semistructured documents

The increasing amount of available semistructured data demands efficient mechanisms to store, process, and search an enormous corpus of data to encourage its global adoption. Current techniques to store semistructured documents either map them to relational databases, or use a combination of flat files and indexes. These two approaches result in a mismatch between the tree-structure of semistructured data and the access characteristics of the underlying storage devices. Furthermore, the inefficiency of XML parsing methods has slowed down the large-scale adoption of XML into actual system implementations. The recent development of lazy parsing techniques is a major step towards improving this situation, but lazy parsers still have significant drawbacks that undermine the massive adoption of XML. ^ Once the processing (storage and parsing) issues for semistructured data have been addressed, another key challenge to leverage semistructured data is to perform effective information discovery on such data. Previous works have addressed this problem in a generic (i.e. domain independent) way, but this process can be improved if knowledge about the specific domain is taken into consideration. ^ This dissertation had two general goals: The first goal was to devise novel techniques to efficiently store and process semistructured documents. This goal had two specific aims: We proposed a method for storing semistructured documents that maps the physical characteristics of the documents to the geometrical layout of hard drives. We developed a Double-Lazy Parser for semistructured documents which introduces lazy behavior in both the pre-parsing and progressive parsing phases of the standard Document Object Model’s parsing mechanism. ^ The second goal was to construct a user-friendly and efficient engine for performing Information Discovery over domain-specific semistructured documents. This goal also had two aims: We presented a framework that exploits the domain-specific knowledge to improve the quality of the information discovery process by incorporating domain ontologies. We also proposed meaningful evaluation metrics to compare the results of search systems over semistructured documents. ^

A domain specific modeling approach for coordinating user-centric communication services

Rapid advances in electronic communication devices and technologies have resulted in a shift in the way communication applications are being developed. These new development strategies provide abstract views of the underlying communication technologies and lead to the so-called user-centric communication applications. One user-centric communication (UCC) initiative is the Communication Virtual Machine (CVM) technology, which uses the Communication Modeling Language (CML) for modeling communication services and the CVM for realizing these services. In communication-intensive domains such as telemedicine and disaster management, there is an increasing need for user-centric communication applications that are domain-specific and that support the dynamic coordination of communication services commonly found in collaborative communication scenarios. However, UCC approaches like the CVM offer little support for the dynamic coordination of communication services resulting from inherent dependencies between individual steps of a collaboration task. Users either have to manually coordinate communication services, or reply on a process modeling technique to build customized solutions for services in a specific domain that are usually costly, rigidly defined and technology specific. ^ This dissertation proposes a domain-specific modeling approach to address this problem by extending the CVM technology with communication-specific abstractions of workflow concepts commonly found in business processes. The extension involves (1) the definition of the Workflow Communication Modeling Language (WF-CML), a superset of CML, and (2) the extension of the functionality of CVM to process communication-specific workflows. The definition of WF-CML includes the meta-model and the dynamic semantics for control constructs and concurrency. We also extended the CVM prototype to handle the modeling and realization of WF-CML models. A comparative study of the proposed approach with other workflow environments validates the claimed benefits of WF-CML and CVM.^

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 1, Issue 1 2007

Fall 2007 Newsletter for FIU's Maps and Imagery User Services department.

MUIS News: Maps and User Imagery Services @ FIU Green Library Vol. 2, Issue 1 2008

Florida International University's Fall 2008 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 2, Issue 2 Spring 2009

Florida International University's Spring 2009 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 3, Issue 1 Fall 2009

Florida International University's Fall 2009 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 3, Issue 2 Fall 2009

Florida International University's Fall 2009 Map and User Imagery Services Newsletter; Vol. 3, issue 2.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 3, Issue 2, Spring 2010

Florida International University's Spring 2010 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 4, Issue 1 Fall 2012

Florida International University's Fall 2012 Map and User Imagery Services Newsletter.

MIUS News: Maps and Imagery User Services @ FIU Green Library: Vol. 4, Issue 2 Spring/Summer 2013

Florida International University's Spring/Summer 2013 Map and User Imagery Services Newsletter.

MIUS News : Maps and Imagery User Services @ FIU Green Library: Vol. 5 Issue 1 Fall 2013

Florida International University's Fall 2013 Map and User Imagery Services Newsletter

Statistical dialog management for health interventions

Research endeavors on spoken dialogue systems in the 1990s and 2000s have led to the deployment of commercial spoken dialogue systems (SDS) in microdomains such as customer service automation, reservation/booking and question answering systems. Recent research in SDS has been focused on the development of applications in different domains (e.g. virtual counseling, personal coaches, social companions) which requires more sophistication than the previous generation of commercial SDS. The focus of this research project is the delivery of behavior change interventions based on the brief intervention counseling style via spoken dialogue systems. ^ Brief interventions (BI) are evidence-based, short, well structured, one-on-one counseling sessions. Many challenges are involved in delivering BIs to people in need, such as finding the time to administer them in busy doctors' offices, obtaining the extra training that helps staff become comfortable providing these interventions, and managing the cost of delivering the interventions. Fortunately, recent developments in spoken dialogue systems make the development of systems that can deliver brief interventions possible. ^ The overall objective of this research is to develop a data-driven, adaptable dialogue system for brief interventions for problematic drinking behavior, based on reinforcement learning methods. The implications of this research project includes, but are not limited to, assessing the feasibility of delivering structured brief health interventions with a data-driven spoken dialogue system. Furthermore, while the experimental system focuses on harmful alcohol drinking as a target behavior in this project, the produced knowledge and experience may also lead to implementation of similarly structured health interventions and assessments other than the alcohol domain (e.g. obesity, drug use, lack of exercise), using statistical machine learning approaches. ^ In addition to designing a dialog system, the semantic and emotional meanings of user utterances have high impact on interaction. To perform domain specific reasoning and recognize concepts in user utterances, a named-entity recognizer and an ontology are designed and evaluated. To understand affective information conveyed through text, lexicons and sentiment analysis module are developed and tested.^

Towards next generation vertical search engines

As the Web evolves unexpectedly fast, information grows explosively. Useful resources become more and more difficult to find because of their dynamic and unstructured characteristics. A vertical search engine is designed and implemented towards a specific domain. Instead of processing the giant volume of miscellaneous information distributed in the Web, a vertical search engine targets at identifying relevant information in specific domains or topics and eventually provides users with up-to-date information, highly focused insights and actionable knowledge representation. As the mobile device gets more popular, the nature of the search is changing. So, acquiring information on a mobile device poses unique requirements on traditional search engines, which will potentially change every feature they used to have. To summarize, users are strongly expecting search engines that can satisfy their individual information needs, adapt their current situation, and present highly personalized search results. ^ In my research, the next generation vertical search engine means to utilize and enrich existing domain information to close the loop of vertical search engine's system that mutually facilitate knowledge discovering, actionable information extraction, and user interests modeling and recommendation. I investigate three problems in which domain taxonomy plays an important role, including taxonomy generation using a vertical search engine, actionable information extraction based on domain taxonomy, and the use of ensemble taxonomy to catch user's interests. As the fundamental theory, ultra-metric, dendrogram, and hierarchical clustering are intensively discussed. Methods on taxonomy generation using my research on hierarchical clustering are developed. The related vertical search engine techniques are practically used in Disaster Management Domain. Especially, three disaster information management systems are developed and represented as real use cases of my research work.^

MIUS News: Maps and Imagery User Services @ FIU Green Library: Volume 6, Issue 1 Spring 2015

Florida International University's Spring 2015 Maps and User Imagery Services Newsletter