Intelligent Systems Laboratory

Information Visualization & Interaction
Building on PARC's deep competencies in UI (user interfaces), HII (human-information interaction), and 3-D visualization and navigation, PARC's approach to information visualization & interaction helps users more easily find relevant and deep information, "connect the dots", focus attention, and counter cognitive biases.

Intelligent & Embedded Reasoning
Hardware and software systems are becoming increasingly complex and expensive, and it is impractical to anticipate every contingency when designing a system. PARC researchers are resolving these issues by applying model-based approaches to system design. The resulting systems can adapt to changing requirements, are simple to design and use, and yet are still able to provide superior functionality and robustness.

Intelligent Control Systems
PARC researchers have designed and are enhancing intelligent control system software. This software coordinates complex, distributed, networked components in modular systems. The technology enables systems such as multifunctional printing systems to intelligently accomplish goals, adapt to system changes, and ensure maximum productivity.

Natural Language
Natural language processing enables machines to understand what people mean and respond with intelligence -- allowing people to interact with a computer naturally and without adapting to a computer's limitations. With over three decades in natural language research and technologies, PARC has developed an approach that goes beyond purely statistical or machine-learning techniques. Our linguistic theories, algorithms, and engineering platforms provide multiple levels of meaning extraction — from language analysis and logic, to deep knowledge representation.

Perceptual Document Analysis
This research focuses on the analysis and interpretation of perceptually salient structure in hand-drawn and mixed printed/hand-drawn documents such as sketched diagrams, annotated printed material, as well as informal material on whiteboards or electronic tablets/PDAs.

Sensemaking
Building on deep competencies in natural language processing and user interfaces/ information visualization & interaction, PARC has developed automated, meaning-based, and user-controlled approaches for analyzing, visualizing, and fluidly interacting with massive, heterogeneous, and often unstructured content collections. PARC's approach supports deeper understanding, better decision making, and greater productivity for a variety of business, search, legal, healthcare, and other complex sensemaking and decision-making tasks.

User Interface Research
The User Interface Research area develops user models and novel user interfaces for information-intensive tasks and collaborations, especially concerning the Internet and its successors. Examples include Information Foraging Theory (a theory of information search behavior) and the Hyperbolic Tree (now sold as a product). One set of studies characterizes, in technical terms, tasks, users, and the computational intermediaries they might use. For example, the area develops models that predict the dynamic changes in users' interest in different information. It also studies how highly interactive visual display media can speed the user's access to information, ability to make sense of it, and time to act on it. Another set of studies invents and implements prototypes of novel components and applications based on the first set of studies.