Event-based personal retrieval

People who work in a research, academic or business environment often have personal information collections which are large enough to need retrieval aids. A major difference between personal information retrieval and normal document retrieval is that the items to be retrieved are often associated with events in the searcher's life and can be retrieved by their relationship to other events as well as by content. This paper describes some of the background to event-based retrieval and then describes a prototype graphical event-based retrieval system

Bilingual episodic memory: an introduction

Our current models of bilingual memory are essentially accounts of semantic memory whose goal is to explain bilingual lexical access to underlying imagistic and conceptual referents. While this research has included episodic memory, it has focused largely on recall for words, phrases, and sentences in the service of understanding the structure of semantic memory. Building on the four papers in this special issue, this article focuses on larger units of episodic memory(from quotidian events with simple narrative form to complex autobiographical memories) in service of developing a model of bilingual episodic memory. This requires integrating theory and research on how culture-specific narrative traditions inform encoding and retrieval with theory and research on the relation between(monolingual) semantic and episodic memory(Schank, 1982; Schank & Abelson, 1995; Tulving, 2002). Then, taking a cue from memory-based text processing studies in psycholinguistics(McKoon & Ratcliff, 1998), we suggest that as language forms surface in the progressive retrieval of features of an event, they trigger further forms within the same language serving to guide a within-language/ within-culture retrieval

A Remember-Know Analysis of the Semantic Serial Position Function

Did the serial position functions observed in certain semantic memory tasks (e.g., remembering the order of books or films) arise because they really tapped episodic memory? To address this issue, participants were asked to make "remember-know" judgments as they reconstructed the release order of the 7 Harry Potter books and 2 sets of movies. For both classes of stimuli, the "remember" and "know" serial position functions were indistinguishable, and all showed the characteristic U-shape with marked primacy and recency effects. These results are inconsistent with a multiple memory systems view, which predicts recency effects only for "remember" responses and no recency effects for "know" responses. However, the data were consistent with a general memory principle account: the relative distinctiveness principle. According to this view, performance on both episodic and semantic memory tasks arises from the same type of processing: Items that are more separated from their close neighbors in psychological space at the time of recall will be better remembered

Why do we remember? The communicative function of episodic memory

Episodic memory has been analyzed in a number of different ways in both philosophy and psychology, and most controversy has centered on its self-referential, ‘autonoetic’ character. Here, we offer a comprehensive characterization of episodic memory in representational terms, and propose a novel functional account on this basis. We argue that episodic memory should be understood as a distinctive epistemic attitude taken towards an event simulation. On this view, episodic memory has a metarepresentational format and should not be equated with beliefs about the past. Instead, empirical findings suggest that the contents of human episodic memory are often constructed in the service of the explicit justification of such beliefs. Existing accounts of episodic memory function that have focused on explaining its constructive character through its role in ‘future-oriented mental time travel’ neither do justice to its capacity to ground veridical beliefs about the past nor to its representational format. We provide an account of the metarepresentational structure of episodic memory in terms of its role in communicative interaction. The generative nature of recollection allows us to represent and communicate the reasons for why we hold certain beliefs about the past. In this process, autonoesis corresponds to the capacity to determine when and how to assert epistemic authority in making claims about the past. A domain where such claims are indispensable are human social engagements. Such engagements commonly require the justification of entitlements and obligations, which is often possible only by explicit reference to specific past events

Sub-types of nonbelieved memories reveal differential outcomes of challenges to memories

Nonbelieved memories (NBMs) highlight the independence between metamemorial judgments that contribute to the experience of remembering. Initial definitions of NBMs portrayed them as involving the withdrawal of autobiographical belief despite sustained recollection. While people rate belief for their NBMs as weaker than recollection, the average difference is too small to support the idea that belief is completely withdrawn in all cases. Furthermore, ratings vary considerably across NBMs. In two studies, we reanalyzed reports from prior studies to examine whether NBM reports reflect a single category or multiple sub-categories using cluster analytic methods. In Study 1, we identified three sub-types of NBMs. In Study 2 we incorporated the concept of belief in accuracy, and found that two of the clusters from Study 1 split into two clusters apiece. Higher ratings of recollection than belief in occurrence characterized all clusters, which were differentiated by the degree of difference between these variables. In both studies the clusters were differentiated by a number of memory characteristic ratings and by reasons reported as leading to the alteration of belief. Implications for understanding the remembering of past events and predicting the creation of NBMs are discussed

Meals described as healthy or unhealthy match public health education in England

Dietary guidelines for the general public aim to lower the incidence of nutrition-related diseases by influencing habitual food choices. Yet little is known about how well the guidelines are matched by the actual practices that people regard as healthy or unhealthy. In the present study, British residents were asked in a cognitive interview to write a description of an occasion when either they ate in an unhealthy way or the eating was healthy. The reported foods and drinks, as well as sort of occasion, location, people present and time of day, were categorised by verbal and semantic similarities. The number of mentions of terms in each category was then contrasted between groups in exact probability tests. Perceived unhealthy and healthy eating occasions differed reliably in the sorts of foods and the contexts reported. There was also full agreement with the national guidelines on eating plenty of fruit and vegetables, eating small amounts of foods and drinks high in fat and/or sugar, drinking plenty of water, and cutting down on alcohol. There was a tendency to regard choices of bread, rice, potatoes, pasta and other starchy foods as healthy. Reported healthy and unhealthy eating did not differ in incidences of meat, fish, eggs, beans and other non-dairy sources of protein or of dairy foods and milk. These results indicate that operationally clear recommendations by health professionals are well understood in this culture but members of the public do not make clear distinctions in the case of foods that can be included in moderate amounts in a healthy diet

Information dynamics algorithm for detecting communities in networks

The problem of community detection is relevant in many scientific disciplines, from social science to statistical physics. Given the impact of community detection in many areas, such as psychology and social sciences, we have addressed the issue of modifying existing well performing algorithms by incorporating elements of the domain application fields, i.e. domain-inspired. We have focused on a psychology and social network - inspired approach which may be useful for further strengthening the link between social network studies and mathematics of community detection. Here we introduce a community-detection algorithm derived from the van Dongen's Markov Cluster algorithm (MCL) method by considering networks' nodes as agents capable to take decisions. In this framework we have introduced a memory factor to mimic a typical human behavior such as the oblivion effect. The method is based on information diffusion and it includes a non-linear processing phase. We test our method on two classical community benchmark and on computer generated networks with known community structure. Our approach has three important features: the capacity of detecting overlapping communities, the capability of identifying communities from an individual point of view and the fine tuning the community detectability with respect to prior knowledge of the data. Finally we discuss how to use a Shannon entropy measure for parameter estimation in complex networks.Comment: Submitted to "Communication in Nonlinear Science and Numerical Simulation