In this paper we present an extractive system that automatically generates gene summaries from the biomedical literature. The proposed text summarization system selects and ranks sentences from multiple MEDLINE abstracts by exploiting gene-specific information and similarity relationships between

This article presents a theory in which automatization is construed as the acquisition of a domain-specific knowledge base, formed of separate representations, instances, of each exposure to the task. Processing is considered automatic if it relies on retrieval of stored instances, which will occur

. The authors then describe the different possible mechanisms that produce automatic, environmental control over these various phenomena and review evidence establishing both the existence of these mechanisms as well as their consequences for judgments, emotions, and

A two-process theory of human information processing is proposed and applied to detection, search, and attention phenomena. Automatic processing is activa-tion of a learned sequence of elements in long-term memory that is initiated by appropriate inputs and then proceeds automatically

We present a system for identifying the semantic relationships, or semantic roles, filled by constituents of a sentence within a semantic frame. Various lexical and syntactic features are derived from parse trees and used to derive statistical classifiers from hand-annotated training data. 1

Many AI researchers are today striving to build agent teams for complex, dynamic multi-agent domains, with intended applications in arenas such as education, training, entertainment, information integration, and collective robotics. Unfortunately, uncertainties in these complex, dynamic domains obstruct coherent teamwork. In particular, team members often encounter differing, incomplete, and possibly inconsistent views of their environment. Furthermore, team members can unexpectedly fail in fulfilling responsibilities or discover unexpected opportunities. Highly flexible coordination and communication is key in addressing such uncertainties. Simply tting individual agents with precomputed coordination plans will not do, for their in flexibility can cause severe failures in teamwork, and their domain-specificity hinders reusability. Our central hypothesis is that the key to such flexibility and reusability isproviding agents with general models of teamwork. Agents exploit such models to autonomously reason about coordination and communication, providing requisite flexibility. Furthermore, the models enable reuse across domains, both saving implementation effort and enforcing consistency. This article presents one general, implemented model of teamwork, called STEAM. The basic building block of teamwork in STEAM is joint intentions (Cohen & Levesque, 1991b); teamwork in STEAM is based on agents' building up a (partial) hierarchy of joint intentions (this hierarchy is seen to parallel Grosz & Kraus's partial Shared-Plans, 1996). Furthermore, in STEAM, team members monitor the team's and individual members' performance, reorganizing the team as necessary. Finally, decision-theoretic communication selectivity in STEAM ensures reduction in communication overheads of teamwork, with appropriate sensitivity to the environmental conditions. This article describes STEAM's application in three different complex domains, and presents detailed empirical results.

The two-process theory of detection, search, and attention presented by Schneider and Shiffrin is tested and extended in a series of experiments. The studies demonstrate the qualitative difference between two modes of information processing: automatic detection and controlled search. They trace

This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, collaborative, and hybrid recommendation approaches. This paper also describes

Active networks allow their users to inject customized programs into the nodes of the network. An extreme case, in which we are most interested, replaces packets with "capsules" -- program fragments that are executed at each network router/switch they traverse. Active architectures permit a massive increase in the sophistication of the computation that is performed within the network. They will enable new applications, especially those based on application-specific multicast, information fusion, and other services that leverage network-based computation and storage. Furthermore, they will accelerate the pace of innovation by decoupling network services from the underlying hardware and allowing new services to be loaded into the infrastructure on demand. In this paper, we describe our vision of an active network architecture, outline our approach to its design, and survey the technologies that can be brought to bear on its implementation. We propose that the research community mount a j...

are predictable only when the control schema can be made explicit. On the production side, the model is con-cerned with the generation of recall and summarization protocols. This process is partly reproductive and partly constructive, involving the inverse operation of the macro-operators. The model is applied