OpenRaiser/Intern-Atlas huggingface dataset:
Comparative evaluation of javascript frameworks
Authors: Andreas Gizas, Sotiris P. Christodoulou, Theodore S. Papatheodorou
Venue: WWW
Year: 2012

For web programmers, it is important to choose the proper JavaScript framework that not only serves their current web project needs, but also provides code of high quality and good performance. The scope of this work is to provide a thorough quality and performance evaluation of the most popular JavaScript frameworks, taking into account well established software quality factors and performance tests. The major outcome is that we highlight the pros and cons of JavaScript frameworks in various areas of interest and signify which and where are the problematical points of their code, that probably need to be improved in the next versions.
User-generated metadata in audio-visual collections
Authors: Riste Gligorov
Venue: WWW
Year: 2012

In recent years, crowdsourcing has gained attention as an alternative method for collecting video annotations. An example is the internet video labeling game Waisda? launched by the Netherlands Institute for Sound and Vision. The goal of this PhD research is to investigate the value of the user tags collected with this video labeling game. To this end, we address the following four issues. First, we perform a comparative analysis between user-generated tags and professional annotations in terms of what aspects of videos they describe. Second, we measure how well user tags are suited for fragment retrieval and compare it with fragment search based on other sources like transcripts and professional annotations. Third, as previous research suggested that user tags predominately refer to objects and rarely describe scenes, we will study whether user tags can be successfully exploited to generate scene-level descriptions. Finally, we investigate how tag quality can be characterized and potential methods to improve it.
Towards situational pattern mining from microblogging activity
Authors: Nathan Gnanasambandam, Keith Thompson, Ion Florie Ho, Sarah S. Lam, Sang Won Yoon
Venue: WWW
Year: 2012

Many useful patterns can be derived from analyzing microblogging behavior at different scales (individual and social group). In this paper, we derive patterns relating to spatio-temporal traffic flow, visit regularity, content and social ties as they relate to an individual's activities in an urban environment (e.g., New York City). We also demonstrate, through an example, methods for reasoning about the activities, locations and group structures that may underlie the microblogging messages in the aforementioned context of mining situation patterns. These individual and group situational patterns may be very crucial when planning for disruptions and organized response.
Partisan scale
Authors: Sedat Gokalp, Hasan Davulcu
Venue: WWW
Year: 2012

US Senate is the venue of political debates where the federal bills are formed and voted. Senators show their support/opposition along the bills with their votes. This information makes it possible to extract the polarity of the senators. We use signed bipartite graphs for modeling debates, and we propose an algorithm for partitioning both the senators, and the bills comprising the debate into binary opposing camps. Simultaneously, our algorithm scales both the senators and the bills on a univariate scale. Using this scale, a researcher can identify moderate and partisan senators within each camp, and polarizing vs. unifying bills. We applied our algorithm on all the terms of the US Senate to the date for longitudinal analysis and developed a web based interactive user interface www.PartisanScale.com to visualize the analysis.
Collecting, reusing and executing private workflows on social network platforms
Authors: Sebastian Görg, Ralph Bergmann, Mirjam Minor, Sarah Gessinger, Siblee Islam
Venue: WWW
Year: 2012

We propose a personal workflow management service as part of a social network that enables private users to construct personal workflows according to their specific needs and to keep track of the workflow execution. Unlike traditional workflows, such personal workflows aim at supporting processes that contain personal tasks and data. Our proposal includes a process-oriented case-based reasoning approach to support private users to obtain an appropriate personal workflow through sharing and reuse of respective experience.
Towards geosocial recommender systems
Authors: Victor de Graaff, Maurice van Keulen, Rolf A. de By
Venue: WWW
Year: 2012

The usage of social networks sites (SNSs), such as Facebook, and geosocial networks (GSNs), such as Foursquare, has increased tremendously over the past years. The willingness of users to share their current locations and experiences facilitate the creation of geographical recommender systems based on user generated content (UGC). This idea has been used to create a substantial amount of geosocial recommender systems (GRSs), such as Gogobot, TripIt, and Trippy already, but can be applied to more complex scenarios, such as the recommendation of products with a strong binding to their region, such as real estate or vacation destinations.
OPAL: a passe-partout for web forms
Authors: Xiaonan Guo, Jochen Kranzdorf, Tim Furche, Giovanni Grasso, Giorgio Orsi, Christian Schallhart
Venue: WWW
Year: 2012

Web forms are the interfaces of the deep web. Though modern web browsers provide facilities to assist in form filling, this assistance is limited to prior form fillings or keyword matching. Automatic form understanding enables a broad range of applications, including crawlers, meta-search engines, and usability and accessibility support for enhanced web browsing. In this demonstration, we use a novel form understanding approach, OPAL, to assist in form filling even for complex, previously unknown forms. OPAL associates form labels to fields by analyzing structural properties in the HTML encoding and visual features of the page rendering. OPAL interprets this labeling and classifies the fields according to a given domain ontology. The combination of these two properties, allows OPAL to deal effectively with many forms outside of the grasp of existing form filling techniques. In the UK real estate domain, OPAL achieves >99% accuracy in form understanding.
S2ORM: exploiting syntactic and semantic information for opinion retrieval
Authors: Liqiang Guo, Xiaojun Wan
Venue: WWW
Year: 2012

Opinion retrieval is the task of finding documents that express an opinion about a given query. A key challenge in opinion retrieval is to capture the query-related opinion score of a document. Existing methods rely mainly on the proximity information between the opinion terms and the query terms to address the key challenge. In this study, we propose to incorporate the syntactic and semantic information of terms into a probabilistic language model in order to capture the query-related opinion score more accurately.
Creating a large-scale searchable digital collection from printed music materials
Authors: Andrew Hankinson, John Ashley Burgoyne, Gabriel Vigliensoni, Ichiro Fujinaga
Venue: WWW
Year: 2012

In this paper we present our work towards developing a large-scale web application for digitizing, recognizing (via optical music recognition), correcting, displaying, and searching printed music texts. We present the results of a recently completed prototype implementation of our workflow process, from document capture to presentation on the web. We discuss a number of lessons learned from this prototype. Finally, we present some open-source Web 2.0 tools developed to provide essential infrastructure components for making searchable printed music collections available online. Our hope is that these experiences and tools will help in creating next-generation globally accessible digital music libraries.
All our messages are belong to us: usable confidentiality in social networks
Authors: Marian Harbach, Sascha Fahl, Thomas Muders, Matthew Smith
Venue: WWW
Year: 2012

Current online social networking (OSN) sites pose severe risks to their users' privacy. Facebook in particular is capturing more and more of a user's past activities, sometimes starting from the day of birth. Instead of transiently passing on information between friends, a user's data is stored persistently and therefore subject to the risk of undesired disclosure. Traditionally, a regular user of a social network has little awareness of her privacy needs in the Web or is not ready to invest a considerable effort in securing her online activities. Furthermore, the centralised nature of proprietary social networking platforms simply does not cater for end-to-end privacy protection mechanisms. In this paper, we present a non-disruptive and lightweight integration of a confidentiality mechanism into OSNs. Additionally, direct integration of visual security indicators into the OSN UI raise the awareness for (un)protected content and thus their own privacy. We present a fully-working prototype for Facebook and an initial usability study, showing that, on average, untrained users can be ready to use the service in three minutes.
Power-law distribution in encoded MFCC frames of speech, music, and environmental sound signals
Authors: Martín Haro, Joan Serrà, Alvaro Corral, Perfecto Herrera
Venue: WWW
Year: 2012

Many sound-related applications use Mel-Frequency Cepstral Coefficients (MFCC) to describe audio timbral content. Most of the research efforts dealing with MFCCs have been focused on the study of different classification and clustering algorithms, the use of complementary audio descriptors, or the effect of different distance measures. The goal of this paper is to focus on the statistical properties of the MFCC descriptor itself. For that purpose, we use a simple encoding process that maps a short-time MFCC vector to a dictionary of binary code-words. We study and characterize the rank-frequency distribution of such MFCC code-words, considering speech, music, and environmental sound sources. We show that, regardless of the sound source, MFCC code-words follow a shifted power-law distribution. This implies that there are a few code-words that occur very frequently and many that happen rarely. We also observe that the inner structure of the most frequent code-words has characteristic patterns. For instance, close MFCC coefficients tend to have similar quantization values in the case of music signals. Finally, we study the rank-frequency distributions of individual music recordings and show that they present the same type of heavy-tailed distribution as found in the large-scale databases. This fact is exploited in two supervised semantic inference tasks: genre and instrument classification. In particular, we obtain similar classification results as the ones obtained by considering all frames in the recordings by just using 50 (properly selected) frames. Beyond this particular example, we believe that the fact that MFCC frames follow a power-law distribution could potentially have important implications for future audio-based applications.
Populating personal linked data caches using context models
Authors: Olaf Hartig, Tom Heath
Venue: WWW
Year: 2012

The emergence of a Web of Data enables new forms of application that require expressive query access, for which mature, Web-scale information retrieval techniques may not be suited. Rather than attempting to deliver expressive query capabilities at Web-scale, this paper proposes the use of smaller, pre-populated data caches whose contents are personalized to the needs of an individual user. We present an approach to a priori population of such caches with Linked Data harvested from the Web, seeded by a simple context model for each user, which is progressively enriched by executing a series of enrichment rules over Linked Data from the Web. Such caches can act as personal data stores supporting a range of different applications. A comprehensive user evaluation demonstrates that our approach can accurately predict the relevance of attributes added to the context model and the execution probability of queries based on these attributes, thereby optimizing the cache population process.
Probabilistic critical path identification for cost-effective monitoring of service-based web applications
Authors: Qiang He, Jun Han, Yun Yang, Jean-Guy Schneider, Hai Jin, Steven Versteeg
Venue: WWW
Year: 2012

The critical path of a composite Web application operating in volatile environments, i.e., the execution path in the service composition with the maximum execution time, should be prioritised in cost-effective monitoring as it determines the response time of the Web application. In volatile operating environments, the critical path of a Web application is probabilistic. As such, it is important to estimate the criticalities of the execution paths, i.e., the probabilities that they are critical, to decide which parts of the system to monitor. We propose a novel approach to the identification of Probabilistic Critical Path for Service-based Web Applications (PCP-SWA), which calculates the criticalities of different execution paths in the context of service composition. We evaluate PCP-SWA experimentally using an example Web application. Compared to random monitoring, PCP-SWA based monitoring is 55.67% more cost-effective on average.
Round-trip semantics with sztakipedia and DBpedia spotlight
Authors: Mihály Héder, Pablo N. Mendes
Venue: WWW
Year: 2012

We describe a tool kit to support a knowledge-enhancement cycle on the Web. In the first step, structured data which is extracted from Wikipedia is used to construct automatic content enhancement engines. Those engines can be used to interconnect knowledge in structured and unstructured information sources on the Web, including Wikipedia itself. Sztakipedia-toolbar is a MediaWiki user script which brings DBpedia Spotlight and other kinds of machine intelligence into the Wiki editor interface to provide enhancement suggestions to the user. The suggestions offered by the tool focus on complementing knowledge and increasing the availability of structured data on Wikipedia. This will, in turn, increase the available information for the content enhancement engines themselves, completing a virtuous cycle of knowledge enhancement.
Exploiting single-user web applications for shared editing: a generic transformation approach
Authors: Matthias Heinrich, Franz Lehmann, Thomas Springer, Martin Gaedke
Venue: WWW
Year: 2012

In the light of the Web 2.0 movement, web-based collaboration tools such as Google Docs have become mainstream and in the meantime serve millions of users. Apart from established collaborative web applications, numerous web editors lack multi-user support even though they are suitable for collaborative work. Enhancing these single-user editors with shared editing capabilities is a costly endeavor since the implementation of a collaboration infrastructure (accommodating conflict resolution, document synchronization, etc.) is required. In this paper, we present a generic transformation approach capable of converting single-user web editors into multi-user editors. Since our approach only requires the configuration of a generic collaboration infrastructure (GCI), the effort to inject shared editing support is significantly reduced in contrast to conventional implementation approaches neglecting reuse. We also report on experimental results of a user study showing that converted editors meet user requirements with respect to software and collaboration qualities. Moreover, we define the characteristics that editors must adhere to in order to leverage the GCI.
A statistical approach to URL-based web page clustering
Authors: Inma Hernández, Carlos R. Rivero, David Ruiz, Rafael Corchuelo
Venue: WWW
Year: 2012

Most web page classifiers use features from the page content, which means that it has to be downloaded to be classified. We propose a technique to cluster web pages by means of their URL exclusively. In contrast to other proposals, we analyze features that are outside the page, hence, we do not need to download a page to classify it. Also, it is non-supervised, requiring little intervention from the user. Furthermore, we do not need to crawl extensively a site to build a classifier for that site, but only a small subset of pages. We have performed an experiment over 21 highly visited websites to evaluate the performance of our classifier, obtaining good precision and recall results.
Heterogeneous web data search using relevance-based on the fly data integration
Authors: Daniel M. Herzig, Thanh Tran
Venue: WWW
Year: 2012

Searching over heterogeneous structured data on the Web is challenging due to vocabulary and structure mismatches among different data sources. In this paper, we study two existing strategies and present a new approach to integrate additional data sources into the search process. The first strategy relies on data integration to mediate mismatches through upfront computation of mappings, based on which queries are rewritten to fit individual sources. The other extreme is keyword search, which does not require any up-front investment, but ignores structure information. Building on these strategies, we present a hybrid approach, which combines the advantages of both. Our approach does not require any upfront data integration, but also leverages the fine grained structure of the underlying data. For a structured query adhering to the vocabulary of just one source, the so-called seed query, we construct an entity relevance model (ERM), which captures the content and the structure of the seed query results. This ERM is then aligned on the fly with keyword search results retrieved from other sources and also used to rank these results. The outcome of our experiments using large-scale real-world data sets suggests that data integration leads to higher search effectiveness compared to keyword search and that our new hybrid approach consistently exceeds both strategies.
Frequent temporal social behavior search in information networks
Authors: Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin
Venue: WWW
Year: 2012

In current social networking service (SNS) such as Facebook, there are diverse kinds of interactions between entity types. One commonly-used activity of SNS users is to track and observe the representative social and temporal behaviors of other individuals. This inspires us to propose a new problem of Temporal Social Behavior Search (TSBS) from social interactions in an information network: given a structural query with associated temporal labels, how to find the subgraph instances satisfying the query structure and temporal requirements? In TSBS, a query can be (a) a topological structure, (b) the partially-assigned individuals on nodes, and/or (c) the temporal sequential labels on edges. The TSBS method consists of two parts: offline mining and online matching. to the former mines the temporal subgraph patterns for retrieving representative structures that match the query. Then based on the given query, we perform the online structural matching on the mined patterns and return the top-k resulting subgraphs. Experiments on academic datasets demonstrate the effectiveness of TSBS.
TripRec: recommending trip routes from large scale check-in data
Authors: Hsun-Ping Hsieh, Cheng-Te Li, Shou-De Lin
Venue: WWW
Year: 2012

With location-based services, such as Foursquare and Gowalla, users can easily perform check-in actions anywhere and anytime. Such check-in data not only enables personal geospatial journeys but also serves as a fine-grained source for trip planning. In this work, we aim to collectively recommend trip routes by leveraging a large-scaled check-in data through mining the moving behaviors of users. A novel recommendation system, TripRec, is proposed to allow users to pecify starting/end and must-go locations. It further provides the flexibility to satisfy certain time constraint (i.e., the expected duration of the trip). By considering a sequence of check-in points as a route, we mine the frequent sequences with some ranking mechanism to achieve the goal. Our TripRec targets at travelers who are unfamiliar to the objective area/city and have time constraints in the trip.
Social status and role analysis of palin's email network
Authors: Xia Hu, Huan Liu
Venue: WWW
Year: 2012

Email usage is pervasive among people from different backgrounds, and email corpus can be an important data source to study intricate social structures. Social status and role analysis on a personal email network can help reveal hidden information. The availability of Sarah Palin's email corpus presents a great opportunity to study social statuses and social roles in an email network. However, the email corpus does not readily lend itself to social network analysis due to problems such as noisy email data, scale in size, and temporal constraints. In this paper, we report an initial investigation of social status and role analysis on Sarah Palin's email corpus. In particular, we conduct a preliminary study on Palin's social statuses and roles. To the best of our knowledge, this work is the first exploration of Sarah Palin's email corpus recently released by the state of Alaska.
Information cascades in social media in response to a crisis: a preliminary model and a case study
Authors: Cindy Hui, Yulia Tyshchuk, William A. Wallace, Malik Magdon-Ismail, Mark K. Goldberg
Venue: WWW
Year: 2012

The focus of this paper is on demonstrating how a model of the diffusion of actionable information can be used to study information cascades on Twitter that are in response to an actual crisis event, and its concomitant alerts and warning messages from emergency managers. We will: identify the types of information requested or shared during a crisis situation; show how messages spread among the users on Twitter including what kinds of information cascades or patterns are observed; and note what these patterns tell us about information flow and the users. We conclude by noting that emergency managers can use this information to either facilitate the spreading of accurate information or impede the flow of inaccurate or improper messages.
ResEval mash: a mashup tool for advanced research evaluation
Authors: Muhammad Imran, Felix Kling, Stefano Soi, Florian Daniel, Fabio Casati, Maurizio Marchese
Venue: WWW
Year: 2012

In this demonstration, we present ResEval Mash, a mashup platform for research evaluation, i.e., for the assessment of the productivity or quality of researchers, teams, institutions, journals, and the like - a topic most of us are acquainted with. The platform is specifically tailored to the need of sourcing data about scientific publications and researchers from the Web, aggregating them, computing metrics (also complex and ad-hoc ones), and visualizing them. ResEval Mash is a hosted mashup platform with a client-side editor and runtime engine, both running inside a common web browser. It supports the processing of also large amounts of data, a feature that is achieved via the sensible distribution of the respective computation steps over client and server. Our preliminary user study shows that ResEval Mash indeed has the power to enable domain experts to develop own mashups (research evaluation metrics); other mashup platforms rather support skilled developers. The reason for this success is ResEval Mash's domain-specificity.