Understanding the Usage and Requirements of the Photo Tagging System

The amount of personal photos is massively increasing and managing them effectively and efficiently requires new approaches and practices. This study analyses the users’ needs and their behaviour towards photo tagging in the context of a personal photo repository. Our results are from a qualitative study with 15 users. Study methods include a questionnaire and a task analy-sis approach in which we analyse and evaluate practices around semi-automated photo tagging. In the task analysis, we describe and use a photo tagging application called SmartImages for studying the actual tagging expe-rience. The results from the study indicate that photo tagging in personal collections is rarely used as it is considered too laborious. The task analysis with SmartImages made users consider tagging worthwhile and beneficial. The results propose changes to the implementation of tagging functionality in photo management applications. We conclude that better visibility of the tagging feature and introducing social elements would improve the usage and benefit of tagging. Providing automated tag suggestions that are comprehen-sible, conceptually relevant and the relation between the displayed tags and the photo is clear would make users more willing to engage with tagging ac-tivities. Addressing the mentioned issues would help the users in managing the increasing number of personal photos.Peer reviewe

Towards context-aware syntax parsing and tagging

Information retrieval (IR) has become one of the most popular Natural Language Processing (NLP) applications. Part of speech (PoS) parsing and tagging plays an important role in IR systems. A broad range of PoS parsers and taggers tools have been proposed with the aim of helping to find a solution for the information retrieval problems, but most of these are tools based on generic NLP tags which do not capture domain-related information. In this research, we present a domain-specific parsing and tagging approach that uses not only generic PoS tags but also domain-specific PoS tags, grammatical rules, and domain knowledge. Experimental results show that our approach has a good level of accuracy when applying it to different domains

From implicit to touching interaction by identification technologies: Towards tagging context

Intelligent environments need interactions capable of detecting users and providing them with good-quality contextual information. In this sense we adapt technologies, identifying and locating people for supporting their needs. However, it is necessary to analyze some important features in order to compare the implicit interaction, which is closer to the users and more natural, to a new interaction by contact. In this paper we present the adaptability of two technologies; Radiofrequency Identification (RFID) and Near Field Communication (NFC). In the first one, the interaction is more appropriate within intelligent environments but in the second one, the same RFID technology, placed in mobile phones, achieves some advantages that we consider to be an intermediate solution until the standardization of sensors arrives.Intelligent environments need interactions capable of detecting users and providing them with good-quality contextual information. In this sense we adapt technologies, identifying and locating people for supporting their needs. However, it is necessary to analyze some important features in order to compare the implicit interaction, which is closer to the users and more natural, to a new interaction by contact. In this paper we present the adaptability of two technologies; Radiofrequency Identification (RFID) and Near Field Communication (NFC). In the first one, the interaction is more appropriate within intelligent environments but in the second one, the same RFID technology, placed in mobile phones, achieves some advantages that we consider to be an intermediate solution until the standardization of sensors arrives

Web 2.0 and folksonomies in a library context

This is the post-print version of the Article. The official published version can be accessed from the link below - Copyright @ 2011 ElsevierLibraries have a societal purpose and this role has become increasingly important as new technologies enable organizations to support, enable and enhance the participation of users in assuming an active role in the creation and communication of information. Folksonomies, a Web 2.0 technology, represent such an example. Folksonomies result from individuals freely tagging resources available to them on a computer network. In a library environment folksonomies have the potential of overcoming certain limitations of traditional classification systems such as the Library of Congress Subject Headings (LCSH). Typical limitations of this type of classification systems include, for example, the rigidity of the underlying taxonomical structures and the difficulty of introducing change in the categories. Folksonomies represent a supporting technology to existing classification systems helping to describe library resources more flexibly, dynamically and openly. As a review of the current literature shows, the adoption of folksonomies in libraries is novel and limited research has been carried out in the area. This paper presents research into the adoption of folksonomies for a University library. A Web 2.0 system was developed, based on the requirements collected from library stakeholders, and integrated with the existing library computer system. An evaluation of the work was carried out in the form of a survey in order to understand the possible reactions of users to folksonomies as well as the effects on their behavior. The broad conclusion of this work is that folksonomies seem to have a beneficial effect on users’ involvement as active library participants as well as encourage users to browse the catalogue in more depth

Towards Cleaning-up Open Data Portals: A Metadata Reconciliation Approach

This paper presents an approach for metadata reconciliation, curation and linking for Open Governamental Data Portals (ODPs). ODPs have been lately the standard solution for governments willing to put their public data available for the society. Portal managers use several types of metadata to organize the datasets, one of the most important ones being the tags. However, the tagging process is subject to many problems, such as synonyms, ambiguity or incoherence, among others. As our empiric analysis of ODPs shows, these issues are currently prevalent in most ODPs and effectively hinders the reuse of Open Data. In order to address these problems, we develop and implement an approach for tag reconciliation in Open Data Portals, encompassing local actions related to individual portals, and global actions for adding a semantic metadata layer above individual portals. The local part aims to enhance the quality of tags in a single portal, and the global part is meant to interlink ODPs by establishing relations between tags.Comment: 8 pages,10 Figures - Under Revision for ICSC201

Towards Universal Semantic Tagging

The paper proposes the task of universal semantic tagging---tagging word tokens with language-neutral, semantically informative tags. We argue that the task, with its independent nature, contributes to better semantic analysis for wide-coverage multilingual text. We present the initial version of the semantic tagset and show that (a) the tags provide semantically fine-grained information, and (b) they are suitable for cross-lingual semantic parsing. An application of the semantic tagging in the Parallel Meaning Bank supports both of these points as the tags contribute to formal lexical semantics and their cross-lingual projection. As a part of the application, we annotate a small corpus with the semantic tags and present new baseline result for universal semantic tagging.Comment: 9 pages, International Conference on Computational Semantics (IWCS

On social networks and collaborative recommendation

Social network systems, like last.fm, play a significant role in Web 2.0, containing large amounts of multimedia-enriched data that are enhanced both by explicit user-provided annotations and implicit aggregated feedback describing the personal preferences of each user. It is also a common tendency for these systems to encourage the creation of virtual networks among their users by allowing them to establish bonds of friendship and thus provide a novel and direct medium for the exchange of data. We investigate the role of these additional relationships in developing a track recommendation system. Taking into account both the social annotation and friendships inherent in the social graph established among users, items and tags, we created a collaborative recommendation system that effectively adapts to the personal information needs of each user. We adopt the generic framework of Random Walk with Restarts in order to provide with a more natural and efficient way to represent social networks. In this work we collected a representative enough portion of the music social network last.fm, capturing explicitly expressed bonds of friendship of the user as well as social tags. We performed a series of comparison experiments between the Random Walk with Restarts model and a user-based collaborative filtering method using the Pearson Correlation similarity. The results show that the graph model system benefits from the additional information embedded in social knowledge. In addition, the graph model outperforms the standard collaborative filtering method.</p