Context generation and information retrieval

The interaction between a user and an information retrieval system can be viewed as a dialogue in which both participants are trying to interpret the others' actions in the light of previous experience. The sys- tem then must try to generate a context in which to interpret the user's response to the presented mate- rial. This notion of context operates on a principle of relevance. Information that the system believes is relevant to the user, or that the user has indicated as relevant will form the basis of the system's notion of the context. This paper presents a way of represent- ing a context that can use both the systems knowl- edge about itself and the user's response to generate a view of the retrieval session

Retrieval cues fail to influence contextualized evaluations.

Initial evaluations generalise to new contexts, whereas counter-attitudinal evaluations are context-specific. Counter-attitudinal information may not change evaluations in new contexts because perceivers fail to retrieve counter-attitudinal cue-evaluation associations from memory outside the counter-attitudinal learning context. The current work examines whether an additional, counter-attitudinal retrieval cue can enhance the generalizability of counter-attitudinal evaluations. In four experiments, participants learned positive information about a target person, Bob, in one context, and then learned negative information about Bob in a different context. While learning the negative information, participants wore a wristband as a retrieval cue for counter-attitudinal Bob-negative associations. Participants then made speeded as well as deliberate evaluations of Bob while wearing or not wearing the wristband. Internal meta-analysis failed to find a reliable effect of the counter-attitudinal retrieval cue on speeded or deliberate evaluations, whereas the context cues influenced speeded and deliberate evaluations. Counter to predictions, counter-attitudinal retrieval cues did not disrupt the generalisation of first-learned evaluations or the context-specificity of second-learned evaluations (Experiments 2-4), but the counter-attitudinal retrieval cue did influence evaluations in the absence of context cues (Experiment 1). The current work provides initial evidence that additional counter-attitudinal retrieval cues fail to disrupt the renewal and generalizability of first-learned evaluations

Mining user activity as a context source for search and retrieval

Nowadays in information retrieval it is generally accepted that if we can better understand the context of users then this could help the search process, either at indexing time by including more metadata or at retrieval time by better modelling the user context. In this work we explore how activity recognition from tri-axial accelerometers can be employed to model a user's activity as a means of enabling context-aware information retrieval. In this paper we discuss how we can gather user activity automatically as a context source from a wearable mobile device and we evaluate the accuracy of our proposed user activity recognition algorithm. Our technique can recognise four kinds of activities which can be used to model part of an individual's current context. We discuss promising experimental results, possible approaches to improve our algorithms, and the impact of this work in modelling user context toward enhanced search and retrieval

Preliminary Experiments using Subjective Logic for the Polyrepresentation of Information Needs

According to the principle of polyrepresentation, retrieval accuracy may improve through the combination of multiple and diverse information object representations about e.g. the context of the user, the information sought, or the retrieval system. Recently, the principle of polyrepresentation was mathematically expressed using subjective logic, where the potential suitability of each representation for improving retrieval performance was formalised through degrees of belief and uncertainty. No experimental evidence or practical application has so far validated this model. We extend the work of Lioma et al. (2010), by providing a practical application and analysis of the model. We show how to map the abstract notions of belief and uncertainty to real-life evidence drawn from a retrieval dataset. We also show how to estimate two different types of polyrepresentation assuming either (a) independence or (b) dependence between the information objects that are combined. We focus on the polyrepresentation of different types of context relating to user information needs (i.e. work task, user background knowledge, ideal answer) and show that the subjective logic model can predict their optimal combination prior and independently to the retrieval process

The information retrieval challenge of human digital memories

Today people are storing increasing amounts of personal information in digital format. While storage of such information is becoming straight forward, retrieval from the vast personal archives that this is creating poses significant challenges. Existing retrieval techniques are good at retrieving from non-personal spaces, such as the World Wide Web. However they are not sufficient for retrieval of items from these new unstructured spaces which contain items that are personal to the individual, and of which the user has personal memories and with which has had previous interaction. We believe that there are new and exciting possibilities for retrieval from personal archives. Memory cues act as triggers for individuals in the remembering process, a better understanding of memory cues will enable us to design new and effective retrieval algorithms and systems for personal archives. Context data, such as time and location, is already proving to play a key part in this special retrieval domain, for example for searching personal photo archives, we believe there are many other rich sources of context that can be exploited for retrieval from personal archives

Applying contextual memory cues for retrieval from personal information archives

Advances in digital technologies for information capture combined with massive increases in the capacity of digital storage media mean that it is now possible to capture and store one’s entire life experiences in a Human Digital Memory (HDM). Information can be captured from a myriad of personal information devices including desktop computers, PDAs, digital cameras, video and audio recorders, and various sensors, including GPS, Bluetooth, and biometric devices. These diverse collections of personal information are potentially very valuable, but will only be so if significant information can be reliably retrieved from them. HDMs differ from traditional document collections for which existing search technologies have been developed since users may have poor recollection of contents or even the existence of stored items. Additionally HDM data is highly heterogeneous and unstructured, making it difficult to form search queries. We believe that a Personal Information Management (PIM) system which exploits the context of information capture, and potentially of earlier refinding, can be valuable in effective retrieval from an HDM. We report an investigation into how individuals perform searches of their personal information, and use the outcome of this study to develop an information retrieval (IR) framework for HDM search incorporating the context of document capture. We then describe the creation of a pilot HDM test collection, and initial experiments in retrieval from this collection. Results from these experiments indicate that use of context data can be significantly beneficial to increasing the efficient retrieval of partially recalled items from an HDM

Brain mechanisms of successful recognition through retrieval of semantic context

Episodic memory is associated with the encoding and retrieval of context information and with a subjective sense of reexperiencing past events. The neural correlates of episodic retrieval have been extensively studied using fMRI, leading to the identification of a "general recollection network" including medial temporal, parietal, and prefrontal regions. However, in these studies, it is difficult to disentangle the effects of context retrieval from recollection. In this study, we used fMRI to determine the extent to which the recruitment of regions in the recollection network is contingent on context reinstatement. Participants were scanned during a cued recognition test for target words from encoded sentences. Studied target words were preceded by either a cue word studied in the same sentence (thus congruent with encoding context) or a cue word studied in a different sentence (thus incongruent with encoding context). Converging fMRI results from independently defined ROIs and whole-brain analysis showed regional specificity in the recollection network. Activity in hippocampus and parahippocampal cortex was specifically increased during successful retrieval following congruent context cues, whereas parietal and prefrontal components of the general recollection network were associated with confident retrieval irrespective of contextual congruency. Our findings implicate medial temporal regions in the retrieval of semantic context, contributing to, but dissociable from, recollective experience

A study of remembered context for information access from personal digital archives

Retrieval from personal archives (or Human Digital Memories (HDMs)) is set to become a significant challenge in information retrieval (IR) research. These archives are unique in that the items in them are personal to the owner and as such the owner may have personal memories associated with the items. It is recognized that the harnessing of an individual’s memories about HDM items can be used as context data (such as user location at the time of item access) to aid retrieval. We present a pilot study, using one subject’s HDM, of remembered context data and its utility in retrieval. Our results explore the types of context data best remembered for different item types and categories over time and show that context appears to become a more important factor in effective HDM IR over time as the subject’s recall of contents declines

Content or context? Searching for musical meaning in task-based interactive information retrieval

Creative professionals search for digital music to accompany moving images using interactive information retrieval systems run by music publishers and record companies. This research investigates the creative professionals and the intermediaries communication processes and information seeking and use behaviour with a view to making recommendations to information retrieval systems builders as to the extent of relative importance of content and contextual factors. A communications model is used to suggest that the meaning of music is determined by its listener and use context, as well as cultural codes and competences. The research is framed by a holistic approach based on Ingwersen and Jarvelin’s Interactive Information Seeking, Retrieval and Behavioral processes model