OpenRaiser/Intern-Atlas huggingface dataset:
Search the past with the portuguese web archive
Authors: Daniel Gomes, David Cruz, João Miranda, Miguel Costa, Simão Fontes
Venue: WWW
Year: 2013

The web was invented to quickly exchange data between scientists, but it became a crucial communication tool to connect the world. However, the web is extremely ephemeral. Most of the information published online becomes quickly unavailable and is lost forever. There are several initiatives worldwide that struggle to archive information from the web before it vanishes. However, search mechanisms to access this information are still limited and do not satisfy their users who demand performance similar to live-web search engines.
Google+ or Google-?: dissecting the evolution of the new OSN in its first year
Authors: Roberto Gonzalez, Rubén Cuevas, Reza Motamedi, Reza Rejaie, Ángel Cuevas
Venue: WWW
Year: 2013

In the era when Facebook and Twitter dominate the market for social media, Google has introduced Google+ (G+) and reported a significant growth in its size while others called it a ghost town. This begs the question that "whether G+ can really attract a significant number of connected and active users despite the dominance of Facebook and Twitter?". This paper tackles the above question by presenting a detailed characterization of G+ based on large scale measurements. We identify the main components of G+ structure, characterize the key features of their users and their evolution over time. We then conduct detailed analysis on the evolution of connectivity and activity among users in the largest connected component (LCC) of G+ structure, and compare their characteristics with other major OSNs. We show that despite the dramatic growth in the size of G+, the relative size of LCC has been decreasing and its connectivity has become less clustered. While the aggregate user activity has gradually increased, only a very small fraction of users exhibit any type of activity. To our knowledge, our study offers the most comprehensive characterization of G+ based on the largest collected data sets.
Combining twitter and media reports on public health events in medisys
Authors: Erik Van der Goot, Hristo Tanev, Jens P. Linge
Venue: WWW
Year: 2013

We describe the harvesting and subsequent analysis of tweets that are linked to media reports on public health events in order to identify which Internet resources are being referred to in these tweets. The aim was to automatically detect resources that are traditionally not considered mainstream media, but play a role in the discussion of public health events on the Internet. Interestingly, our initial evaluation of the results showed that most references related to public health events lead to traditional news media sites, even though URLs to non-traditional media receive a higher rank. We will briefly describe the Medical Information System (MedISys) and the methodology used to obtain and analyse tweets.
Effective web scraping with OXPath
Authors: Giovanni Grasso, Tim Furche, Christian Schallhart
Venue: WWW
Year: 2013

Even in the third decade of the Web, scraping web sites remains a challenging task: Most scraping programs are still developed as ad-hoc solutions using a complex stack of languages and tools. Where comprehensive extraction solutions exist, they are expensive, heavyweight, and proprietary.
Course-specific search engines: semi-automated methods for identifying high quality topic-specific corpora
Authors: Neel Guha, Matt Wytock
Venue: WWW
Year: 2013

Web search is an important research tool for many high school courses. However, generic search engines have a number of problems that arise out of not understanding the context of search (the high school course), leading to results that are off-topic or inappropriate as reference material. In this paper, we introduce the concept of a course-specific search engine and build such a search engine for the Advanced Placement US History (APUSH) course; the results of which are preferred by subject matter experts (high school teachers) over existing search engines. This reference search engine for APUSH relies on a hand-curated set of sites picked specifically for this educational context. In order to automate this expensive process, we describe two algorithms for indentifying high quality topical sites using an authoritative source such as a textbook: one based on textual similarity and another using structured data from knowledge bases. Initial experimental results indicate that these algorithms can successfully classify high quality documents leading to the automatic creation of topic-specific corpora for any course.
Fast centrality-driven diffusion in dynamic networks
Authors: Abraão Guimarães, Alex Borges Vieira, Ana Paula Couto da Silva, Artur Ziviani
Venue: WWW
Year: 2013

Diffusion processes in complex dynamic networks can arise, for instance, on data search, data routing, and information spreading. Therefore, understanding how to speed up the diffusion process is an important topic in the study of complex dynamic networks. In this paper, we shed light on how centrality measures and node dynamics coupled with simple diffusion models can help on accelerating the cover time in dynamic networks. Using data from systems with different characteristics, we show that if dynamics is disregarded, network cover time is highly underestimated. Moreover, using centrality accelerates the diffusion process over a different set of complex dynamic networks when compared with the random walk approach. For the best case, in order to cover 80% of nodes, fast centrality-driven diffusion reaches an improvement of 60%, i.e. when next-hop nodes are selected by using centrality measures. Additionally, we also propose and present the first results on how link prediction can help on speeding up the diffusion process in dynamic networks.
A concept for generating simplified RESTful interfaces
Authors: Markus Gulden, Stefan Kugele
Venue: WWW
Year: 2013

Today, innovative companies are forced to evolve their software systems faster and faster, either for providing customer services and products or for supporting internal processes. At the same time, already existing, maybe even legacy systems are crucial for different reasons and by that cannot be abolished easily. While integrating legacy software into new systems in general is considered by well-known approaches like SOA (service-oriented architecture), at the best of our knowledge, it lacks of ways to make legacy systems available for remote clients like smart phones or embedded devices.
Addressing the privacy management crisis in online social networks
Authors: Krishna P. Gummadi
Venue: WWW
Year: 2013

The sharing of personal data has emerged as a popular activity over online social networking sites like Facebook. As a result, the issue of online social network privacy has received significant attention in both the research literature and the mainstream media. Our overarching goal is to improve defaults and provide better tools for managing privacy, but we are limited by the fact that the full extent of the privacy problem remains unknown; there is little quantification of the incidence of incorrect privacy settings or the difficulty users face when managing their privacy. In this talk, I will first focus on measuring the disparity between the desired and actual privacy settings, quantifying the magnitude of the problem of managing privacy. Later, I will discuss how social network analysis techniques can be leveraged towards addressing the privacy management crisis.
Learning to recommend with multi-faceted trust in social networks
Authors: Lei Guo, Jun Ma, Zhumin Chen
Venue: WWW
Year: 2013

Traditionally, trust-aware recommendation methods that utilize trust relations for recommender systems assume a single type of trust between users. However, this assumption ignores the fact that trust as a social concept inherently has many aspects. A user may place trust differently to different people. Motivated by this observation, we propose a novel probabilistic factor analysis method, which learns the multi-faceted trust relations and user profiles through a shared user latent feature space. Experimental results on the real product rating data set show that our approach outperforms state-of-the-art methods on the RMSE measure.
Mining and analyzing the enterprise knowledge graph
Authors: Ido Guy
Venue: WWW
Year: 2013

Today's enterprises hold ever-growing amounts of public data, stemming from different organizational systems, such as development environments, CRM systems, business intelligence systems, and enterprise social media. This data unlocks rich and diverse information about entities, people, terms, and the relationships among them. A lot of insight can be gained through analyzing this knowledge graph, both by individual employees and by the organization as a whole. In this talk, I will review recent work done by the Social Technologies & Analytics group at IBM Research-Haifa to mine these relationships, represent them in a generalized model, and use the model for different aims within the enterprise, including social search [5], expertise location [1], social recommendation [2, 3], and network analysis [4].
A machine-to-machine architecture to merge semantic sensor measurements
Authors: Amelie Gyrard
Venue: WWW
Year: 2013

The emerging field Machine-to-Machine (M2M) enables machines to communicate with each other without human intervention. Existing semantic sensor networks are domain-specific and add semantics to the context. We design a Machine-to-Machine (M2M) architecture to merge heterogeneous sensor networks and we propose to add semantics to the measured data rather than to the context. This architecture enables to: (1) get sensor measurements, (2) enrich sensor measurements with semantic web technologies, domain ontologies and the Link Open Data, and (3) reason on these semantic measurements with semantic tools, machine learning algorithms and recommender systems to provide promising applications.
The STAC (security toolbox: attacks & countermeasures) ontology
Authors: Amelie Gyrard, Christian Bonnet, Karima Boudaoud
Venue: WWW
Year: 2013

We present a security ontology to help non-security expert software designers or developers to: (1) design secure software and, (2) to understand and be aware of main security concepts and issues. Our security ontology defines the main security concepts such as attacks, countermeasures, security properties and their relationships. Countermeasures can be cryptographic concepts (encryption algorithm, key management, digital signature, hash function), security tools or security protocols. The purpose of this ontology is to be reused in numerous domains such as security of web applications, network management or communication networks (sensor, cellular and wireless). The ontology and a user interface (to use the ontology) are available online.
Political hashtag hijacking in the U.S
Authors: Asmelash Teka Hadgu, Venkata Rama Kiran Garimella, Ingmar Weber
Venue: WWW
Year: 2013

We study the change in polarization of hashtags on Twitter over time and show that certain jumps in polarity are caused by "hijackers" engaged in a particular type of hashtag war.
A pilot study of cyber security and privacy related behavior and personality traits
Authors: Tzipora Halevi, James Lewis, Nasir D. Memon
Venue: WWW
Year: 2013

Recent research has begun to focus on the factors that cause people to respond to phishing attacks as well as affect user behavior on social networks. This study examines the correlation between the Big Five personality traits and email phishing response. Another aspect examined is how these factors relate to users' tendency to share information and protect their privacy on Facebook (which is one of the most popular social networking sites).
Measuring personalization of web search
Authors: Aniko Hannak, Piotr Sapiezynski, Arash Molavi Kakhki, Balachander Krishnamurthy, David Lazer, Alan Mislove, Christo Wilson
Venue: WWW
Year: 2013

Web search is an integral part of our daily lives. Recently, there has been a trend of personalization in Web search, where different users receive different results for the same search query. The increasing personalization is leading to concerns about Filter Bubble effects, where certain users are simply unable to access information that the search engines' algorithm decides is irrelevant. Despite these concerns, there has been little quantification of the extent of personalization in Web search today, or the user attributes that cause it. In light of this situation, we make three contributions. First, we develop a methodology for measuring personalization in Web search results. While conceptually simple, there are numerous details that our methodology must handle in order to accurately attribute differences in search results to personalization. Second, we apply our methodology to 200 users on Google Web Search; we find that, on average, 11.7% of results show differences due to personalization, but that this varies widely by search query and by result ranking. Third, we investigate the causes of personalization on Google Web Search. Surprisingly, we only find measurable personalization as a result of searching with a logged in account and the IP address of the searching user. Our results are a first step towards understanding the extent and effects of personalization on Web search engines today.
Using SKOS vocabularies for improving web search
Authors: Bernhard Haslhofer, Flávio Martins, João Magalhães
Venue: WWW
Year: 2013

Knowledge organization systems such as thesauri or taxonomies are increasingly being expressed using the Simple Knowledge Organization System (SKOS) and published as structured data on the Web. Search engines can exploit these vocabularies and improve search by expanding terms at query or document indexing time. We propose a SKOS-based term expansion and scoring technique that leverages labels and semantic relationships of SKOS concept definitions. We also implemented this technique for Apache Lucene and Solr. Experiments with the Medical Subject Headings vocabulary and an early evaluation with Library of Congress Subject Headings indicated gains in precision when using SKOS-based expansion compared to pseudo relevance feedback and no expansion. Our findings are important for publishers and consumer of Web vocabularies who want to use them for improving search over Web documents.
ResourceSync: leveraging sitemaps for resource synchronization
Authors: Bernhard Haslhofer, Simeon Warner, Carl Lagoze, Martin Klein, Robert Sanderson, Michael L. Nelson, Herbert Van de Sompel
Venue: WWW
Year: 2013

Many applications need up-to-date copies of collections of changing Web resources. Such synchronization is currently achieved using ad-hoc or proprietary solutions. We propose ResourceSync, a general Web resource synchronization protocol that leverages XML Sitemaps. It provides a set of capabilities that can be combined in a modular manner to meet local or community requirements. We report on work to implement this protocol for arXiv.org and also provide an experimental prototype for the English Wikipedia as well as a client API.
Exploiting annotations for the rapid development of collaborative web applications
Authors: Matthias Heinrich, Franz Josef Grüneberger, Thomas Springer, Martin Gaedke
Venue: WWW
Year: 2013

Web application frameworks are a proven means to accelerate the development of interactive web applications. However, implementing collaborative real-time applications like Google Docs requires specific concurrency control services (i.e. document synchronization and conflict resolution) that are not included in prevalent general-purpose frameworks like jQuery or Knockout. Hence, developers have to get familiar with specific collaboration frameworks (e.g. ShareJS) which substantially increases the development effort. To ease the development of collaborative web applications, we propose a set of source code annotations representing a lightweight mechanism to introduce concurrency control services into mature web frameworks. Those annotations are interpreted at runtime by a dedicated collaboration engine to sync documents and resolve conflicts. We enhanced the general-purpose framework Knockout with a collaboration engine and conducted a developer study comparing our approach to a traditional concurrency control library. The evaluation results show that the effort to incorporate collaboration capabilities into a web application can be reduced by up to 40 percent using the annotation-based solution.
Analyzing the suitability of web applications for a single-user to multi-user transformation
Authors: Matthias Heinrich, Franz Lehmann, Franz Josef Grüneberger, Thomas Springer, Martin Gaedke
Venue: WWW
Year: 2013

Multi-user web applications like Google Docs or Etherpad are crucial to efficiently support collaborative work (e.g. jointly create texts, graphics, or presentations). Nevertheless, enhancing single-user web applications with multi-user capabilities (i.e. document synchronization and conflict resolution) is a time-consuming and intricate task since traditional approaches adopting concurrency control libraries (e.g. Apache Wave) require numerous scattered source code changes. Therefore, we devised the Generic Collaboration Infrastructure (GCI) [8] that is capable of converting single-user web applications non-invasively into collaborative ones, i.e. no source code changes are required. In this paper, we present a catalog of vital application properties that allows determining if a web application is suitable for a GCI transformation. On the basis of the introduced catalog, we analyze 12 single-user web applications and show that 6 are eligible for a GCI transformation. Moreover, we demonstrate (1) the transformation of one qualified application, namely, the prominent text editor TinyMCE, and (2) showcase the resulting multi-user capabilities. Both demo parts are illustrated in a dedicated screencast that is available at http://vsr.informatik.tu-chemnitz.de/demo/TinyMCE/.
Using explicit discourse rules to guide video enrichment
Authors: Michiel Hildebrand, Lynda Hardman
Venue: WWW
Year: 2013

Video content analysis and named entity extraction are increasingly used to automatically generate content annotations for TV programs. A potential use of these annotations is to provide an entry point to background information that users can consume on a second screen. Automatic enrichments are, however, meaningless when it is unclear to the user what they can do with them and why they would. We propose to contextualize the annotations by an explicit representation of discourse in the form of scene templates. Through content rules these templates are populated with the relevant annotations. We illustrate this idea with an example video and annotations generated in the LinkedTV1 project.
FANS: face annotation by searching large-scale web facial images
Authors: Steven C. H. Hoi, Dayong Wang, I. Yeu Cheng, Elmer Weijie Lin, Jianke Zhu, Ying He, Chunyan Miao
Venue: WWW
Year: 2013

Auto face annotation is an important technique for many real-world applications, such as online photo album management, new video summarization, and so on. It aims to automatically detect human faces from a photo image and further name the faces with the corresponding human names. Recently, mining web facial images on the internet has emerged as a promising paradigm towards auto face annotation. In this paper, we present a demonstration system of search-based face annotation: FANS - Face ANnotation by Searching large-scale web facial images. Given a query facial image for annotation, we first retrieve a short list of the most similar facial images from a web facial image database, and then annotate the query facial image by mining the top-ranking facial images and their corresponding labels with sparse representation techniques. Our demo system was built upon a large-scale real-world web facial image database with a total of 6,025 persons and about 1 million facial images. This paper demonstrates the potential of searching and mining web-scale weakly labeled facial images on the internet to tackle the challenging face annotation problem, and addresses some open problems for future exploration by researchers in web community. The live demo of FANS is available online at http://msm.cais.ntu.edu.sg/FANS/.
Web usage mining with semantic analysis
Authors: Laura Hollink, Peter Mika, Roi Blanco
Venue: WWW
Year: 2013

Web usage mining has traditionally focused on the individual queries or query words leading to a web site or web page visit, mining patterns in such data. In our work, we aim to characterize websites in terms of the semantics of the queries that lead to them by linking queries to large knowledge bases on the Web. We demonstrate how to exploit such links for more effective pattern mining on query log data. We also show how such patterns can be used to qualitatively describe the differences between competing websites in the same domain and to quantitatively predict website abandonment.
The linked data platform (LDP)
Authors: Arnaud Le Hors, Steve Speicher
Venue: WWW
Year: 2013

As a result of the Linked Data Basic Profile submission, made by several organizations including IBM, EMC, and Oracle, the W3C launched in June 2012 the Linked Data Platform (LDP) Working Group (WG).
Linked data selectors
Authors: Kai Michael Höver, Max Mühlhäuser
Venue: WWW
Year: 2013

In the world of Linked Data, HTTP URIs are names. A URI is dereferenced to obtain a copy or description of the referred resource. If only a fragment of a resource should be referred, pointing to the whole resource is not sufficient. Therefore, it is necessary to be able to refer to fragments of resources, and to name them with URIs to interlink them in the Web of Data. This is especially helpful in the educational context where learning processes including discussion and social interaction demand for exact references and granular selections of media. This paper presents the specification of Linked Data Selectors, an OWL ontology for describing dereferenceable fragments of Web resources.
Organizational overlap on social networks and its applications
Authors: Cho-Jui Hsieh, Mitul Tiwari, Deepak Agarwal, Xinyi (Lisa) Huang, Sam Shah
Venue: WWW
Year: 2013

Online social networks have become important for networking, communication, sharing, and discovery. A considerable challenge these networks face is the fact that an online social network is partially observed because two individuals might know each other, but may not have established a connection on the site. Therefore, link prediction and recommendations are important tasks for any online social network. In this paper, we address the problem of computing edge affinity between two users on a social network, based on the users belonging to organizations such as companies, schools, and online groups. We present experimental insights from social network data on organizational overlap, a novel mathematical model to compute the probability of connection between two people based on organizational overlap, and experimental validation of this model based on real social network data. We also present novel ways in which the organization overlap model can be applied to link prediction and community detection, which in itself could be useful for recommending entities to follow and generating personalized news feed.
Space-efficient data structures for Top-k completion
Authors: Bo-June Paul Hsu, Giuseppe Ottaviano
Venue: WWW
Year: 2013

Virtually every modern search application, either desktop, web, or mobile, features some kind of query auto-completion. In its basic form, the problem consists in retrieving from a string set a small number of completions, i.e. strings beginning with a given prefix, that have the highest scores according to some static ranking. In this paper, we focus on the case where the string set is so large that compression is needed to fit the data structure in memory. This is a compelling case for web search engines and social networks, where it is necessary to index hundreds of millions of distinct queries to guarantee a reasonable coverage; and for mobile devices, where the amount of memory is limited.