We have devized a methodology that mines sequential navigation patterns from a website's logs to enable us to identify the most signi cant associative links in the networks. Spreading activation can then be applied to the generated network of weighted hyperlinks enabling the content-dependent, semantic retrieval of nodes in the network. This approach to information retrieval avoids many of the ...

For the update summaries task of the Text Analysis Conference 2008 we have implemented a novel summarization technique based on query expansion with encyclopedic knowledge and activation spreading in a large document graph. We have also experimented with sentence compression for building the summaries. The results are average – ranked 27 out of 58 for responsiveness in manual evaluation – but w...

We propose a framework for deterministic simulation of user behavior that allows to analyze the cost-gain-based performance on single result lists or whole search sessions. The ideal user representing optimal behavior (i.e., most gain with lowest effort) is contrasted with more “average” users that employ the spreading activation model from cognitive theory. On TREC Session Track data, the idea...

A spreading activation model is proposed for the purpose of automatically merging databases with heterogeneous indexing systems. An overview of the connectionist approaches in information retrieval (IR) is discussed. Then, spreading activation models of IR are compared with the vector space models that have been widely adopted in the development of IR systems. Based upon the review of the previ...

An eecient retrieval of a relatively small number of relevant cases from a huge case base is a crucial subtask of Case-Based Reasoning (CBR). In this article, we present Case Retrieval Nets, a memory model that has recently been developed for this task. The main idea is to apply a spreading activation process to the case memory structured as a Case Retrieval Net in order to retrieve cases being...

Associative theories of learning have been used to explain human contingency learning since the 1980’s. Recent findings have led several authors to claim that there is no evidence clearly showing the engagement of associative processes of acquisition or representation in human contingency learning, and to propose non-associative accounts. Priming techniques can detect associative representation...

Learners have different knowledge, interests and also goals in any educational process. If all the learners are provided the same content the process will probably not meet expected goals. A personalized approach to a learner increases the efficiency of the learning process. It is based on information about the learner that is subject of change. Several adaptive educational systems exist. Howev...

In this paper, we present SGDB, a graph database with a storage model optimized for computation of Spreading Activation (SA) queries. The primary goal of the system is to minimize the execution time of spreading activation algorithm over large graph structures stored on a persistent media; without pre-loading the whole graph into the memory. We propose a storage model aiming to minimize number ...

This article sets forth a detailed theoretical proposal of how the truth of ordinary empirical statements, often atomic in form, is computed. The method of computation draws on psychological concepts such as those of associative networks and spreading activation, rather that the concepts of philosophical or logical theories of truth. Axioms for a restricted class of cases are given, as well as ...

Techniques that traditionally have been useful for retrieving same domain analogies from small single use knowledge bases such as spreading activation and indexing on selected features are inadequate for retrieving cross domain analogies from large multi use knowledge bases In this paper we describe Knowledge Directed Spreading Activation KDSA a new method for retriev ing analogies in a large s...