What do people want from their lifelogs?

The practice of lifelogging potentially consists of automatically capturing and storing a digital record of every piece of information that a person (lifelogger) encounters in their daily experiences. Lifelogging has become an increasingly popular area of research in recent years. Most current lifeloggiing research focuses on techniques for data capture or processing. Current applications of lifelogging technology are usually driven by new technology inventions, creative ideas of researchers, or the special needs of a particular user group, e.g. individuals with memory impairment. To the best of our knowledge, little work has explored potential lifelogs applications from the perspective of the desires of the general public. One of the difficulties of carrying out such a study is the balancing of the information given to the subject regarding lifelog technology to enable them to generate realistic ideas without limiting or directing their imaginations by providing too much specific information. We report a study in which we take a progressive approach where we introduce lifelogging in three stages, and collect the ideas and opinions of a volunteer group of general public participants on techniques for lifelog capture, and applications and functionality

Integrating memory context into personal information re-finding

Personal information archives are emerging as a new challenge for information retrieval (IR) techniques. The user’s memory plays a greater role in retrieval from person archives than from other more traditional types of information collection (e.g. the Web), due to the large overlap of its content and individual human memory of the captured material. This paper presents a new analysis on IR of personal archives from a cognitive perspective. Some existing work on personal information management (PIM) has begun to employ human memory features into their IR systems. In our work we seek to go further, we assume that for IR in PIM system terms can be weighted not only by traditional IR methods, but also taking the user’s recall reliability into account. We aim to develop algorithms that combine factors from both the system side and the user side to achieve more effective searching. In this paper, we discuss possible applications of human memory theories for this algorithm, and present results from a pilot study and a proposed model of data structure for the HDMs achieves

A strategy for evaluating search of “Real” personal information archives

Personal information archives (PIAs) can include materials from many sources, e.g. desktop and laptop computers, mobile phones, etc. Evaluation of personal search over these collections is problematic for reasons relating to the personal and private nature of the data and associated information needs and measuring system response effectiveness. Conventional information retrieval (IR) evaluation involving use of Cranfield type test collections to establish retrieval effectiveness and laboratory testing of interactive search behaviour have to be re-thought in this situation. One key issue is that personal data and information needs are very different to search of more public third party datasets used in most existing evaluations. Related to this, understanding the issues of how users interact with a search system for their personal data is important in developing search in this area on a well grounded basis. In this proposal we suggest an alternative IR evaluation strategy which preserves privacy of user data and enables evaluation of both the accuracy of search and exploration of interactive search behaviour. The general strategy is that instead of a common search dataset being distributed to participants, we suggest distributing standard expandable personal data collection, indexing and search tools to non-intrusively collect data from participants conducting search tasks over their own data collections on their own machines, and then performing local evaluation of individual results before central agregation

Exploring Digital Elements for Visualizing Time in Personal Information Re-finding

Psychological theories on memory of time suggest that people naturally remember ‘events’ rather than the ‘dates’ and ‘hours’. These features are, however, usually required by computer applications for desktop search (information re-finding) tasks. This explains why ‘time’ features are not well remembered for desktop search, as reported in some studies. In order to improve on this situation, we proposed our iCLIPS browser interface, which enables user re-fining initial search results using a suggestive timeline, where visualization elements representing landmark events and important computer activities were displayed. These visual elements on the time line were expected to act as episodic memory cues to help users recollect their search target by recognizing their episodic context. This interface is built on top of a personal search engine providing a unified index of all the information a user has encountered or created, such as documents, web pages, email, and personal photos. We present a pilot study to explore the types of these visual. The result and suggestions for future main study were discussed

Memory support for desktop search

The user's memory plays a very important role in desktop search. A search query with insufficiently or inaccurately recalled information may make the search dramatically less effective. In this paper, we discuss three approaches to support user’s memory during desktop search. These include extended types of well remembered search options, the use of past search queries and results, and search from similar items. We will also introduce our search system which incorporates these features

Segmenting and summarizing general events in a long-term lifelog

Lifelogging aims to capture a person’s life experiences using digital devices. When captured over an extended period of time a lifelog can potentially contain millions of files from various sources in a range of formats. For lifelogs containing such massive numbers of items, we believe it is important to group them into meaningful sets and summarize them, so that users can search and browse their lifelog data efficiently. Existing studies have explored the segmentation of continuously captured images over short periods of at most a few days into small groups of “events” (episodes). Yet, for long-term lifelogs, higher levels of abstraction are desirable due to the very large number of “events” which will occur over an extended period. We aim to segment a long-term lifelog at the level of general events which typically extend beyond a daily boundary, and to select summary information to represent these events. We describe our current work on higher level segmentation and summary information extraction for long term life logs and report a preliminary pilot study on a real long-term lifelog collection

DCU linking runs at MediaEval 2012: search and hyperlinking task

We describe Dublin City University (DCU)'s participation in the Hyperlinking sub-task of the MediaEval 2012 Search and Hyperlinking Task. Our strategy involves combining textual metadata, automatic speech recognition (ASR) transcripts, and visual content analysis to create anchor summaries for each video segment available for linking. Two categories of fusion strategy, score-based and rank-based methods, were used to combine scores from different modalities to produce potential inter-item links

Mechanical performance and fracture behavior of Fe₄₁Co₇Cr₁₅Mo₁₄Y₂C₁₅B₆ bulk metallic glass

The mechanical properties of a new Fe₄₁Co₇Cr₁₅Mo₁₄Y₂C₁₅B₆ bulk glassy alloy were studied by impact bending, compression, and hardness tests carried out at room temperature. The compressive fracture strength, elastic strain to fracture, Young’s modulus and Vickers hardness were measured to be 3.5 GPa, 1.5%, 265 GPa, and 1253 kg mm⁻², respectively. The fracture mode of the glassy alloy under uniaxial compression is different from those of other bulk metallic glasses in that this fracture mode causes the samples to be broken, in an exploding manner, into a large number of micrometer-scale pieces. The fracture mechanisms of this bulk glassy alloy under bending and uniaxial compression are discussed based on the observation of the fracture surfaces. Vickers indentation tests indicate that the structure of the glassy ingot may be inhomogeneous

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

Information access tasks and evaluation for personal lifelogs

Emerging personal lifelog (PL) collections contain permanent digital records of information associated with individuals’ daily lives. This can include materials such as emails received and sent, web content and other documents with which they have interacted, photographs, videos and music experienced passively or created, logs of phone calls and text messages, and also personal and contextual data such as location (e.g. via GPS sensors), persons and objects present (e.g. via Bluetooth) and physiological state (e.g. via biometric sensors). PLs can be collected by individuals over very extended periods, potentially running to many years. Such archives have many potential applications including helping individuals recover partial forgotten information, sharing experiences with friends or family, telling the story of one’s life, clinical applications for the memory impaired, and fundamental psychological investigations of memory. The Centre for Digital Video Processing (CDVP) at Dublin City University is currently engaged in the collection and exploration of applications of large PLs. We are collecting rich archives of daily life including textual and visual materials, and contextual context data. An important part of this work is to consider how the effectiveness of our ideas can be measured in terms of metrics and experimental design. While these studies have considerable similarity with traditional evaluation activities in areas such as information retrieval and summarization, the characteristics of PLs mean that new challenges and questions emerge. We are currently exploring the issues through a series of pilot studies and questionnaires. Our initial results indicate that there are many research questions to be explored and that the relationships between personal memory, context and content for these tasks is complex and fascinating