Intelligent Information Processing -- Projects

Audio Hot Spotting

Automated Information Discovery and Retrieval from Asian Language Sources

Distributed Resource Brokering in Complex Network Environments

Foundations for Next Generation Information Access

Robot Platoon Command and Control

Social Information Retrieval

Web Ontology Language (OWL)

Intelligent Information Processing

Intelligent Information Processing investigates technologies, tools, and processes that support the discovery, processing, exploitation, and dissemination of information, tools and knowledge. Intelligent agents are covered in this area.

Audio Hot Spotting

Qian Hu, Principal Investigator

Bedford and Washington

Problem
Large volumes of recordings require rapid retrieval of segments potentially relevant to a given query (audio hot spotting). Because of high automatic speech recognition (ASR) word error rates and the loss of important audio information in speech transcription, spoken document retrieval systems that simply combine ASR with information retrieval (IR) do not meet this need in real applications.

Objectives
We propose to research and develop audio-specific retrieval algorithms in critical domains by (1) exploiting multiple types of acoustic information from the audio signals; (2) exploring several adaptive techniques to improve existing ASR performance; and (3) fusing component technologies such as ASR, language/speaker identification, audio feature extraction, and information retrieval.

Activities
We will research algorithms and techniques to extend and improve ASR and audio feature extraction and to develop audio-based query algorithms making use of the multiple types of audio information. We will research and develop fusion algorithms to build an audio hot spotting system based on the extended ASR, audio feature extraction, language/speaker identification, and the new audio query language.

Impacts
Our research in audio hot spotting algorithms and prototype development will address the needs of MITRE sponsors with warehouses of recordings waiting for efficient retrieval. It will extend MITRE's information retrieval capability from text to include audio. The expertise gained through the research will equip MITRE to better advise industry developers and our sponsors on audio information retrieval topics and evaluation standards.

Automated Information Discovery and Retrieval from Asian Language Sources

Ray LeBlanc, Principal Investigator

Bedford and Washington

Problem
While several commercial capabilities exist to address particular facets of machine translation (MT) needs, emphasis has been placed on European-based languages. Furthermore, none of the existing COTS products are particularly well suited to the military environment. English translation of Asian languages is much more difficult than translation of European languages and has presented the MT community with significant challenges.

Objectives
This project will develop a capability to perform Chinese and Korean cross-language information retrieval, information discovery (ID), data mining (DM), and knowledge management (KM) in support of open source intelligence analysis. The project will develop a prototype capability that can support in-field experimentation with a broad spectrum of users.

Activities
We will provide an automated capability to translate electronic textual information between Chinese and English, and between Korean and English. We will characterize and subsequently retrieve information, based on user specified profiles, from Chinese- and Korean-language sources by means of a prototype analytic tool. A dictionary management capability will allow users to build, import/export, and aggregate custom dictionaries.

Impacts
This project has the potential for improving the efficiency and effectiveness of intelligence organizations currently impacted by foreign language translation issues. It is expected to provide the beneficiaries with needed interim capabilities and validation of the most fertile areas for the future application of government funds.

Distributed Resource Brokering in Complex Network Environments

Paul Silvey, Principal Investigator

Bedford and Washington

Problem
Many challenging problems facing MITRE's sponsors require the coordinated use of large numbers of distributed IT resources. Hard computational problems such as data mining become tractable when thousands of computers are simultaneously brought to bear. Likewise, global information management architectures, like those envisioned for a Joint Battlespace Infosphere, require distributed infrastructures to be sufficiently scalable, fault-tolerant, and timely.

Objectives
We are investigating the performance of various proposed techniques for distributed resource discovery in peer-to-peer (P2P) networks by modeling and simulating them in realistic complex network environments. By studying many approaches in many situations, we aim to discover fundamental principles that designers of distributed IT systems can use to achieve desired levels of performance in particular real-world environments.

Activities
To prepare for experimentation, we are developing models of resource brokers that capture essential aspects of their collective performance in a society of brokers, such as index size and granularity, breadth of resource and topic coverage, supply and demand loading, referral network topology, etc. We are simultaneously developing network environment models ranging from simple and static to complex and dynamic.

Impacts
Our sponsors will be affected by the changes that network centric, distributed, and P2P technologies are bringing to resource discovery and management problems. Dynamic information management in intelligence, logistics, weather reporting, and command and control all face scalability and timeliness challenges that centralized content indexing approaches will not completely solve. This research will help improve our understanding of key issues.

Foundations for Next Generation Information Access

Warren Greiff, Principal Investigator

Bedford and Washington

Problem
Computerized support for information gathering is fragmented across multiple research communities, and integration is difficult due to the lack of an underlying formalism that cuts across the different technologies. Statistical techniques for individual components have been developed in isolation and without a common theoretical foundation. As a result we are left with a number of reasonably effective, semi-principled, incompatible techniques.

Objectives
The principal objective is the development of statistical foundations for information access. A successful foundation will comprise rigorous characterizations of the issues of modeling and estimation, together with principled methodologies for adapting to new languages, genres, information domains, auxiliary knowledge sources, and tasks.

Activities
We will develop simulations that model the stochastic generation of latent document features, observable document features, the determination of document relevance, and the distribution of query characteristics. We will perform exploratory data analysis on available research corpora to verify our models. A central focus will be on research into the importance of variance reduction and the potential benefits of various bias-variance strategies.

Impacts
This research is directly relevant to existing MITRE projects. The results will allow MITRE to develop information access systems incorporating new sources of evidence and to tailor information systems to meet specific military and intelligence needs. MITRE will then be strategically positioned to set the direction of research into, and development of, next-generation information access technology.

  
Robot Platoon Command and Control

Alan Christiansen, Principal Investigator

Washington

Problem
Reliable autonomous soldier robot teams will not be possible for many years. However, an intermediate level of autonomy, where a commander gives high-level commands (e.g., “Go to the top of Hill 203”), is achievable in the near future. This supervisory control requires only occasional intervention by a commander during a mission.

Objectives
This proposal asserts that one human is adequate for directing a small team of robots. Validating the assertion will require us to demonstrate a working team system where robots exhibit some automated reasoning (route planning, navigation) and cooperative behavior, while attending to human guidance. We will use reconnaissance tasks in urban terrain as our testbed.

Activities
We will extend behavior-based robotics approaches to include the memory and communication required for human participation in the team. Our principal demonstration task will be to produce a team entry for the RoboCup-Rescue annual competition. We will also investigate the utility of platform mobility for reconnaissance-directed sensor networks.

Impacts
MITRE’s capability in robotics will be of considerable importance to our customers in the near future. This proposal builds on MITRE’s current expertise in command and control and artificial intelligence. Robot platoon command and control defines a niche that is a natural extension of this expertise.

Social Information Retrieval

Raymond D'Amore, Principal Investigator

Washington

Problem
Our research centers on developing new technology for tracking Internet-based networked organizations, and using those results to identify potential vulnerabilities and threats. Current information retrieval technology does not directly address the problem of detecting activist networks, assessing behavior, and tracking their evolution; new technology is needed to detect networks based on their structure and context.

Objectives
The main objective is to develop technology for a worldwide monitoring system used to detect the emergence of new groups (e.g., activists) and track the evolution of existing organizations based on their online activity. The focus will be on assessing an organization's behavior and its vulnerabilities.

Activities
We are exploring the confluence of information retrieval for collecting distributed information, social network analysis for determining network structure and characteristics, and dynamical systems modeling for determining network function or behavior. Work includes the development of advanced smart crawler collection tools that will use adaptive and cooperative searching techniques to provide efficient and high-coverage collection from the Web or other network search environments.

Impacts
This research will provide new tools for detecting emergent networked organizations in the open Web and enterprise environments, and will provide a basis for modeling their behavior and identifying critical nodes for assessing vulnerabilities and network robustness. Our initial work has already had impact on several sponsor mission areas.

Web Ontology Language (OWL)

DARPA Office: IXO
DARPA PM: Mr. Murray A. Burke

Roger L. Costello, Principal Investigator

Bedford and Washington

Problem
Interoperability is difficult when we use different terms;for example, “guarantee” versus “warranty.” Will a machine be able to dynamically realize that these terms mean the same thing? How do we define the semantics of a vocabulary in a way that will enable machines to dynamically realize that two terms are the same or are related (and how they are related)? Solving this problem will go a long way toward achieving the vision of the Semantic Web.

Objectives
For several years DARPA has been working on an XML-based language to enhance interoperability by defining the semantics of vocabulary. An outcome of their work is the Web Ontology Language (OWL). MITRE has been asked to develop a PowerPoint-based tutorial that explains in a clear fashion the OWL and OWL-Light ontology languages.

Activities
A PowerPoint tutorial will be developed, including complete, validated examples. The culmination of the work will be a tutorial that is presented to DARPA.

Impacts
The resulting tutorial will be made available Internet-wide. It will enable the Internet community to quickly attain expertise in this technology. The consequence will be increased skill levels on ontologies, and (hopefully) increased interoperability. From a corporate perspective this will be great public relations for both MITRE and DARPA.