Toward conceptual indexing using automatic assignment of descriptors

Indexing techniques have reached a well maturated state. Digital libraries and other digital collections make an intense use of these algorithms to store and retrieve documents. In the other side, we have browsing techniques, which lets the user to gather the information. Current approaches are not yet advanced enough in order to satisfy the user. At CERN we are working in a indexer based on thesaurus descriptors. With a collection of documents related to thesaurus, user can manipulate them in a more conceptual way. Here we describe the core of this system, the automatic descriptor assigner

The best of both worlds: highlighting the synergies of combining manual and automatic knowledge organization methods to improve information search and discovery.

Research suggests organizations across all sectors waste a significant amount of time looking for information and often fail to leverage the information they have. In response, many organizations have deployed some form of enterprise search to improve the 'findability' of information. Debates persist as to whether thesauri and manual indexing or automated machine learning techniques should be used to enhance discovery of information. In addition, the extent to which a knowledge organization system (KOS) enhances discoveries or indeed blinds us to new ones remains a moot point. The oil and gas industry was used as a case study using a representative organization. Drawing on prior research, a theoretical model is presented which aims to overcome the shortcomings of each approach. This synergistic model could help to re-conceptualize the 'manual' versus 'automatic' debate in many enterprises, accommodating a broader range of information needs. This may enable enterprises to develop more effective information and knowledge management strategies and ease the tension between what arc often perceived as mutually exclusive competing approaches. Certain aspects of the theoretical model may be transferable to other industries, which is an area for further research

Creating sparks: comparing search results using discriminatory search term word co-occurrence to facilitate serendipity in the enterprise.

Categories or tags that appear in faceted search interfaces which are representative of an information item, rarely convey unexpected or non-obvious associated concepts buried within search results. No prior research has been identified which assesses the usefulness of discriminative search term word co-occurrence to generate facets to act as catalysts to facilitate insightful and serendipitous encounters during exploratory search. In this study, 53 scientists from two organisations interacted with semi-interactive stimuli, 74% expressing a large/moderate desire to use such techniques within their workplace. Preferences were shown for certain algorithms and colour coding. Insightful and serendipitous encounters were identified. These techniques appear to offer a significant improvement over existing approaches used within the study organisations, providing further evidence that insightful and serendipitous encounters can be facilitated in the search user interface. This research has implications for organisational learning, knowledge discovery and exploratory search interface design

Demonstration of Hierarchical Document Clustering of Digital Library Retrieval Results

As digital libraries grow in size, querying their contents will become as frustrating as querying the web is now. One remedy is to hierarchically cluster the results that are returned by searching a digital library. We demonstrate the clustering of search results from Carnegie Mellon's Informedia database, a large video library that supports indexing and retrieval with automatically generated descriptors

Demonstration of Hierarchical Document Clustering of Digital Library Retrieval Results

As digital libraries grow in size, querying their contents will become as frustrating as querying the web is now. One remedy is to hierarchically cluster the results that are returned by searching a digital library. We demonstrate the clustering of search results from Carnegie Mellons Informedia database, a large video library that supports indexing and retrieval with automatically generated descriptors

Re-examining and re-conceptualising enterprise search and discovery capability: towards a model for the factors and generative mechanisms for search task outcomes.

Many organizations are trying to re-create the Google experience, to find and exploit their own corporate information. However, there is evidence that finding information in the workplace using search engine technology has remained difficult, with socio-technical elements largely neglected in the literature. Explication of the factors and generative mechanisms (ultimate causes) to effective search task outcomes (user satisfaction, search task performance and serendipitous encountering) may provide a first step in making improvements. A transdisciplinary (holistic) lens was applied to Enterprise Search and Discovery capability, combining critical realism and activity theory with complexity theories to one of the worlds largest corporations. Data collection included an in-situ exploratory search experiment with 26 participants, focus groups with 53 participants and interviews with 87 business professionals. Thousands of user feedback comments and search transactions were analysed. Transferability of findings was assessed through interviews with eight industry informants and ten organizations from a range of industries. A wide range of informational needs were identified for search filters, including a need to be intrigued. Search term word co-occurrence algorithms facilitated serendipity to a greater extent than existing methods deployed in the organization surveyed. No association was found between user satisfaction (or self assessed search expertise) with search task performance and overall performance was poor, although most participants had been satisfied with their performance. Eighteen factors were identified that influence search task outcomes ranging from user and task factors, informational and technological artefacts, through to a wide range of organizational norms. Modality Theory (Cybersearch culture, Simplicity and Loss Aversion bias) was developed to explain the study observations. This proposes that at all organizational levels there are tendencies for reductionist (unimodal) mind-sets towards search capability leading to fixes that fail. The factors and mechanisms were identified in other industry organizations suggesting some theory generalizability. This is the first socio-technical analysis of Enterprise Search and Discovery capability. The findings challenge existing orthodoxy, such as the criticality of search literacy (agency) which has been neglected in the practitioner literature in favour of structure. The resulting multifactorial causal model and strategic framework for improvement present opportunities to update existing academic models in the IR, LIS and IS literature, such as the DeLone and McLean model for information system success. There are encouraging signs that Modality Theory may enable a reconfiguration of organizational mind-sets that could transform search task outcomes and ultimately business performance

Just-in-time Information Interfaces: A new Paradigm for Information Discovery and Exploration

We live in a time of increasing information overload. Described as “a byproduct of the lack of maturity of the information age” (Spira & Goldes, 2007), information overload can be painful, and harm our concentration - the resulting choice overload impacts out decision-making abilities. Given the problem of information overload, and the unsatisfying nature of human-information interaction using traditional browsing or keyword-based search, this research investigates how the design of just-in-time information services can improve the user experience of goal-driven interactions with information. This thesis explores the design of just-in-time information services through the iterative development of two strands of high-level prototypes (FMI and KnowDis). I custombuilt both prototype systems for the respective evaluations, which have then been conducted as part of a series of lab-based eye-tracking studies (FMI) as well as two field studies (KnowDis). The lab-based eye-tracking studies were conducted with 100 participants measuring task performance, user satisfaction, and gaze behaviour. The lab studies found that the FMI prototype design did improve the performance aspect of the user experience for all participants and improved the usability aspect of the user experience for novice participants. However, the FMI prototype design seemed to be less effective and usable for expert participants. Two field studies were conducted as part of a two-year research collaboration, which lasted a total of 10 weeks and involved approximately 70 knowledge workers overall from across the globe. As part of those field studies, 46 semi-structured interviews were also conducted. The field studies found that the KnowDis prototype design did improve the user experience for participants overall by making work-related information search more efficient. However, while the KnowDis prototype design was useful for some knowledge workers and even integrated seamlessly into their day-to-day work, it appeared to be less useful and even distracting to others