8,663 research outputs found
Collaborative video searching on a tabletop
Almost all system and application design for multimedia systems is based around a single user working in isolation to perform some task yet much of the work for which we use computers to help us, is based on working collaboratively with colleagues. Groupware systems do support user collaboration but typically this is supported through software and users still physically work independently. Tabletop systems, such as the DiamondTouch from MERL, are interface devices which support direct user collaboration on a tabletop. When a tabletop is used as the interface for a multimedia system, such as a video search system, then this kind of direct collaboration raises many questions for system design. In this paper we present a tabletop system for supporting a pair of users in a video search task and we evaluate the system not only in terms of search performance but also in terms of userāuser interaction and how different user personalities within each pair of searchers impacts search performance and user interaction. Incorporating the user into the system evaluation as we have done here reveals several interesting results and has important ramifications for the design of a multimedia search system
Metadata enrichment for digital heritage: users as co-creators
This paper espouses the concept of metadata enrichment through an expert and user-focused approach to metadata creation and management. To this end, it is argued the Web 2.0 paradigm enables users to be proactive metadata creators. As Shirky (2008, p.47) argues Web 2.0ās social tools enable āaction by loosely structured groups, operating without managerial direction and outside the profit motiveā. Lagoze (2010, p. 37) advises, āthe participatory nature of Web 2.0 should not be dismissed as just a popular phenomenon [or fad]ā. Carletti (2016) proposes a participatory digital cultural heritage approach where Web 2.0 approaches such as crowdsourcing can be sued to enrich digital cultural objects. It is argued that āheritage crowdsourcing, community-centred projects or other forms of public participationā. On the other hand, the new collaborative approaches of Web 2.0 neither negate nor replace contemporary standards-based metadata approaches. Hence, this paper proposes a mixed metadata approach where user created metadata augments expert-created metadata and vice versa. The metadata creation process no longer remains to be the sole prerogative of the metadata expert. The Web 2.0 collaborative environment would now allow users to participate in both adding and re-using metadata. The case of expert-created (standards-based, top-down) and user-generated metadata (socially-constructed, bottom-up) approach to metadata are complementary rather than mutually-exclusive. The two approaches are often mistakenly considered as dichotomies, albeit incorrectly (Gruber, 2007; Wright, 2007) .
This paper espouses the importance of enriching digital information objects with descriptions pertaining the about-ness of information objects. Such richness and diversity of description, it is argued, could chiefly be achieved by involving users in the metadata creation process. This paper presents the importance of the paradigm of metadata enriching and metadata filtering for the cultural heritage domain. Metadata enriching states that a priori metadata that is instantiated and granularly structured by metadata experts is continually enriched through socially-constructed (post-hoc) metadata, whereby users are pro-actively engaged in co-creating metadata. The principle also states that metadata that is enriched is also contextually and semantically linked and openly accessible. In addition, metadata filtering states that metadata resulting from implementing the principle of enriching should be displayed for users in line with their needs and convenience. In both enriching and filtering, users should be considered as prosumers, resulting in what is called collective metadata intelligence
Automatically building research reading lists
All new researchers face the daunting task of familiarizing themselves with the existing body of research literature in their respective fields. Recommender algorithms could aid in preparing these lists, but most current algorithms do not understand how to rate the importance of a paper within the literature, which might limit their effectiveness in this domain. We explore several methods for augmenting exist-ing collaborative and content-based filtering algorithms with measures of the influence of a paper within the web of cita-tions. We measure influence using well-known algorithms, such as HITS and PageRank, for measuring a nodeās im-portance in a graph. Among these augmentation methods is a novel method for using importance scores to influence collaborative filtering. We present a task-centered evalua-tion, including both an offline analysis and a user study, of the performance of the algorithms. Results from these stud-ies indicate that collaborative filtering outperforms content-based approaches for generating introductory reading lists
Towards a Cloud-Based Service for Maintaining and Analyzing Data About Scientific Events
We propose the new cloud-based service OpenResearch for managing and
analyzing data about scientific events such as conferences and workshops in a
persistent and reliable way. This includes data about scientific articles,
participants, acceptance rates, submission numbers, impact values as well as
organizational details such as program committees, chairs, fees and sponsors.
OpenResearch is a centralized repository for scientific events and supports
researchers in collecting, organizing, sharing and disseminating information
about scientific events in a structured way. An additional feature currently
under development is the possibility to archive web pages along with the
extracted semantic data in order to lift the burden of maintaining new and old
conference web sites from public research institutions. However, the main
advantage is that this cloud-based repository enables a comprehensive analysis
of conference data. Based on extracted semantic data, it is possible to
determine quality estimations, scientific communities, research trends as well
the development of acceptance rates, fees, and number of participants in a
continuous way complemented by projections into the future. Furthermore, data
about research articles can be systematically explored using a content-based
analysis as well as citation linkage. All data maintained in this
crowd-sourcing platform is made freely available through an open SPARQL
endpoint, which allows for analytical queries in a flexible and user-defined
way.Comment: A completed version of this paper had been accepted in SAVE-SD
workshop 2017 at WWW conferenc
The State-of-the-arts in Focused Search
The continuous influx of various text data on the Web requires search engines to improve their retrieval abilities for more specific information. The need for relevant results to a userās topic of interest has gone beyond search for domain or type specific documents to more focused result (e.g. document fragments or answers to a query). The introduction of XML provides a format standard for data representation, storage, and exchange. It helps focused search to be carried out at different granularities of a structured document with XML markups. This report aims at reviewing the state-of-the-arts in focused search, particularly techniques for topic-specific document retrieval, passage retrieval, XML retrieval, and entity ranking. It is concluded with highlight of open problems
Contextualised Browsing in a Digital Library's Living Lab
Contextualisation has proven to be effective in tailoring \linebreak search
results towards the users' information need. While this is true for a basic
query search, the usage of contextual session information during exploratory
search especially on the level of browsing has so far been underexposed in
research. In this paper, we present two approaches that contextualise browsing
on the level of structured metadata in a Digital Library (DL), (1) one variant
bases on document similarity and (2) one variant utilises implicit session
information, such as queries and different document metadata encountered during
the session of a users. We evaluate our approaches in a living lab environment
using a DL in the social sciences and compare our contextualisation approaches
against a non-contextualised approach. For a period of more than three months
we analysed 47,444 unique retrieval sessions that contain search activities on
the level of browsing. Our results show that a contextualisation of browsing
significantly outperforms our baseline in terms of the position of the first
clicked item in the result set. The mean rank of the first clicked document
(measured as mean first relevant - MFR) was 4.52 using a non-contextualised
ranking compared to 3.04 when re-ranking the result lists based on similarity
to the previously viewed document. Furthermore, we observed that both
contextual approaches show a noticeably higher click-through rate. A
contextualisation based on document similarity leads to almost twice as many
document views compared to the non-contextualised ranking.Comment: 10 pages, 2 figures, paper accepted at JCDL 201
- ā¦