Presents principles of dialog cooperativity derived from a corpus of task-oriented spoken human-machine dialog. Analyzes the "corpus" to produce a set of dialog design principles intended to prevent users from having to initiate clarification and repair metacommunication that the system would not understand. Proposes a "more…

Presents a taxonomy of jokes and wit as a useful, descriptive tool. Argues that humor processing may occur in a parallel rather than serial fashion by contrasting a serial-processing, incongruity-resolution model with an alternative dual-processing model. Also presents a taxonomy of the social functions of wit. (JK)

Tests how well two models of text comprehension (one referential and one causal) predicted the importance ratings and the recall of procedural texts. Finds better predictive power of the causal model for importance ratings; neither model performed well with recall; and neither model was as predictive of procedural text as they were in previous…

Offers a brief overview of the Structure Building Framework, a simple framework for describing the cognitive processes and mechanisms involved in discourse comprehension. Reviews the seminal work on which it is based (the first decade of structure-building research); and recounts the research conducted by the author to test the Structure Building…

Hypothesizes a resonance process in which concepts and propositions in the discourse resonate in response to related elements in the current sentence, initiating a process that makes available a subset of the information in the representation. Reviews research; presents explicit assumptions about the discourse representation; and describes results…

Analyzes the distribution of 33 linguistic markers of complexity across 23 spoken and written registers of English. Identifies a five-dimensional model and uses it to describe the complexity characteristics of spoken and written registers. Finds that, whereas written registers exhibit profiles differing widely in extent and kind of complexity,…

Contributes to communication theory and research by adding to a discussion of a computational model called latent semantic analysis (LSA). Argues that LSA does not handle all aspects of language processing, but offers a biologically and psychologically plausible mechanistic explanation of the acquisition, induction, and representation of verbal…

Describes the seven main components of QUEST, a cognitive model of question answering that attempts to simulate the answers adults produce when they answer different types of questions, both closed class and open class. Illustrates how the model could be applied to different types of knowledge structures, including causal networks, goal…

Tests the QUEST model of question answering in two experiments. Examines which components of QUEST could predict good answers to why-questions and how-questions in the context of short stories. Supports the validity of arc-search procedures and structural distance for both question categories. Finds only partial support for number of information…

Tests the QUEST model of question answering in naturalistic settings and in settings with complex pragmatic constraints: telephone surveys, business interactions, filmed interviews, and interviews on popular television programs. Finds that QUEST explains most of the answers in these contexts and virtually all of the answers that refer to the…

Describes a recursive transition network model that analyzes and represents a story as a causal network of categorized clauses and labeled relations. Reports on two experiments using procedural criteria to identify inferences and the assumptions that inferences operate over distances in the text and are transitive, resulting in a network…

Introduces a multistate probabilistic causal chain notation for describing the knowledge structures implicitly represented by the subjective conditional probability distribution. Proposes a psychological process model of how story comprehension and recall processes operate using causal chain representations. Compares the model's story-recall…

Determines the nature of time constraints under which readers generate superordinate goal inferences. Provides support for a global-coherence model of inference generation which argues for the importance of causal information in constructing a coherent text representation. (HB)

Investigates the hypothesis that one of the processes used in situation model development is an inferential process in which the reader employs knowledge to form expectations when predictive text opportunities arise. Suggests that predictions are available to the reader at an abstract level of representation. (HB)

Describes a computational model of high-dimensional context space: the Hyperspace Analog to Language (HAL). Shows that HAL provides sufficient information to make semantic, grammatical, and abstract distinctions. Demonstrates the cognitive compatibility of the representations with human processing; and introduces a new methodology that extracts…