Inferring user intent in web search by exploiting social annotations

This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval, http://dx.doi.org/10.1145/1835449.1835636In this paper, we present a folksonomy-based approach for implicit user intent extraction during a Web search process. We present a number of result re-ranking techniques based on this representation that can be applied to any Web search engine. We perform a user experiment the results of which indicate that this type of representation is better at context extraction than using the actual textual content of the document.This research was partially supported by the Spanish Ministry of Science and Education (TIN2008-06566-C04-02) and the Regional Government of Madrid (S2009TIC-1542)

Harvesting community tags and annotations to augment institutional repository metadata

One of the greatest challenges facing managers of institutional repositories today is the cost of providing high quality, precise metadata that satisfies the search requirements of their many different user groups. Social tagging systems such as Flickr, del.icio.us, Connotea and You.tube enable communities to tag photos, web pages, scientific publications and videos with organically-evolved, community relevant vocabularies and to share their tags through the Web. But is there a way that repository managers can exploit these new community tagging movements to enhance their collections’ metadata? If users are provided with simple tagging services, can they be encouraged to generate meaningful, useful metadata that can then be harvested and exploited? This presentation will describe a number of semantic tagging and annotation services that we have developed for open repositories of social sciences and humanities data (indigenous collections, linguistic recordings, publications). It will also discuss possible solutions to the associated social and technical challenges that include: motivating users to attach annotations; ensuring quality control and authentication of the annotations; techniques for harvesting meaningful useful metadata (using OAI PMH); exploiting the secondary metadata to improve the search and browse capabilities over the repositories; differentiating between primary and secondary metadata in the presentation of search results

Komplex hálózatok vizsgálata statisztikus fizikai módszerekkel = Analysis of complex networks with statistical physics methods

Hálózati csoportosulásokat (klasztereket, modulokat) kereső módszer segítségével átfedő, sűrű csoportokat találtunk molekuláris biológiai (fehérje-fehérje kölcsönhatások, transzkripció reguláció), kognitív (szó-asszociációs) és szociális (társszerzőségi) hálózatokban. A hálózati modulkeresővel megtalált átfedő csoportosulásokat a hálózati csúcspontokról rendelkezésre álló információk (pl. a fehérjék funkciója) alapján statisztikai tesztekkel ellenőriztük. A modulok segítségével fehérje-fehérje kölcsönhatási hálózatokban megjósoltuk korábban ismeretlen funkciójú fehérjék funkcióját és jósoltunk fehérje csoportokat, amelyek valószínűleg eddig ismeretlen speciális biológiai feladatok elvégzésén együttműködnek. Az átfedő modulkereső módszer irányított és súlyozott hálózatokra való kiterjesztésével azonosítottuk az irányított hálózatok két fő típusát (az átfedések irányába illetve azokból kifelé mutató modulok esete) és lehetővé tettük a súlyozott hálózatokban történő pontosabb modulkeresést. | With a network module search technique, we identified overlapping modules (also called: clusters, communities) of nodes in complex networks from molecular biology (protein-protein interactions and transcription regulation), cognitive science (word association web) and social science (co-authorship web). We verified the identified overlapping network modules by using additional information available about the nodes (e.g., the annotations of proteins) and performing statistical tests. Based on the modules in protein-protein interaction networks we predicted functions for proteins with no known functions so far and also pointed out groups of proteins that are likely to collaborate on specific biological tasks that are not yet known. By extending the overlapping network module search method to directed and weighted graphs, we have uncovered two major types of overlapping directed modular structure (modules pointing towards the overlaps and modules pointing outwards) and have enabled a more precise module search in weighted networks

Query independent measures of annotation and annotator impact

The modern-day web-user plays a far more active role in the creation of content for the web as a whole. In this paper we present Annoby, a free-text annotation system built to give users a more interactive experience of the events of the Rugby World Cup 2007. Annotations can be used for query-independent ranking of both the annotations and the original recorded video footage (or documents) which has been annotated, based on the social interactions of a community of users. We present two algorithms, AuthorRank and MessageRank, designed to take advantage of these interactions so as to provide a means of ranking documents by their social impact

A linked data-driven & service-oriented architecture for sharing educational resources

The two fundamental aims of managing educational resources are to enable resources to be reusable and interoperable and to enable Web-scale sharing of resources across learning communities. Currently, a variety of approaches have been proposed to expose and manage educational resources and their metadata on the Web. These are usually based on heterogeneous metadata standards and schemas, such as IEEE LOM or ADL SCORM, and diverse repository interfaces such as OAI-PMH or SQI. Also, there is still a lack of usage of controlled vocabularies and available data sets that could replace the widespread use of unstructured text for describing resources. On the other hand, the Linked Data approach has proven that it offers a set of successful principles that have the potential to alleviate the aforementioned issues. In this paper, we introduce an architecture and prototype which is fundamentally based on (a) Linked Data principles and (b) Service-orientation to resolve the integration issues for sharing educational resources

Soft peer review: social software and distributed scientific evaluation

The debate on the prospects of peer-review in the Internet age and the increasing criticism leveled against the dominant role of impact factor indicators are calling for new measurable criteria to assess scientific quality. Usage-based metrics offer a new avenue to scientific quality assessment but face the same risks as first generation search engines that used unreliable metrics (such as raw traffic data) to estimate content quality. In this article I analyze the contribution that social bookmarking systems can provide to the problem of usage-based metrics for scientific evaluation. I suggest that collaboratively aggregated metadata may help fill the gap between traditional citation-based criteria and raw usage factors. I submit that bottom-up, distributed evaluation models such as those afforded by social bookmarking will challenge more traditional quality assessment models in terms of coverage, efficiency and scalability. Services aggregating user-related quality indicators for online scientific content will come to occupy a key function in the scholarly communication system

Accurator: Nichesourcing for Cultural Heritage

With more and more cultural heritage data being published online, their usefulness in this open context depends on the quality and diversity of descriptive metadata for collection objects. In many cases, existing metadata is not adequate for a variety of retrieval and research tasks and more specific annotations are necessary. However, eliciting such annotations is a challenge since it often requires domain-specific knowledge. Where crowdsourcing can be successfully used for eliciting simple annotations, identifying people with the required expertise might prove troublesome for tasks requiring more complex or domain-specific knowledge. Nichesourcing addresses this problem, by tapping into the expert knowledge available in niche communities. This paper presents Accurator, a methodology for conducting nichesourcing campaigns for cultural heritage institutions, by addressing communities, organizing events and tailoring a web-based annotation tool to a domain of choice. The contribution of this paper is threefold: 1) a nichesourcing methodology, 2) an annotation tool for experts and 3) validation of the methodology and tool in three case studies. The three domains of the case studies are birds on art, bible prints and fashion images. We compare the quality and quantity of obtained annotations in the three case studies, showing that the nichesourcing methodology in combination with the image annotation tool can be used to collect high quality annotations in a variety of domains and annotation tasks. A user evaluation indicates the tool is suited and usable for domain specific annotation tasks