OpenRaiser/Intern-Atlas huggingface dataset:
Size matters: word count as a measure of quality on wikipedia
Authors: Joshua Evan Blumenstock
Venue: WWW
Year: 2008

Wikipedia, free encyclopedia, now contains over two million English articles, and is widely regarded as a high-quality, authoritative encyclopedia. Some Wikipedia articles, however, are of questionable quality, and it is not always apparent to the visitor which articles are good and which are bad. We propose a simple metric -- word count -- for measuring article quality. In spite of its striking simplicity, we show that this metric significantly outperforms the more complex methods described in related work.
Emergence of terminological conventions as an author-searcher coordination game
Authors: David Bodoff, Sheizaf Rafaeli
Venue: WWW
Year: 2008

All information exchange on the Internet -- whether through full text, controlled vocabularies, ontologies, or other mechanisms -- ultimately requires that that an information provider and seeker use the same word or symbol. In this paper, we investigate what happens when both searchers and authors are dynamically choosing terms to match the other side. With each side trying to anticipate the other, does a terminological convention ever emerge, or do searchers and providers continue to miss potential partners through mis-match of terms? We use a game-theoretic setup to frame questions, and learning theory to make predictions about whether and which term will emerge as a convention.
Value-driven design for "infosuasive" web applications
Authors: Davide Bolchini, Franca Garzotto, Paolo Paolini
Venue: WWW
Year: 2008

An infosuasive web application is mainly intended to be at the same time informative and persuasive, i.e., it aims at supporting knowledge needs and it has also the (declared or not declared) goal of influencing user's opinions, attitudes and behaviors. Most web applications, in fact, are infosuasive (except those whose aim is mainly operational). In this paper, we investigate the complex set of elements that informs the very early design of infosuasive web applications. We propose a conceptual framework aimed at supporting the actors involved in this process to integrate their different viewpoints, to organize the variety of issues that need to be analyzed, to find a direction in the numerous design options, and to represent the results of this activity in an effective way.
Location and the web (LocWeb 2008)
Authors: Susanne Boll, Christopher B. Jones, Eric Kansa, Puneet Kishor, Mor Naaman, Ross Purves, Arno Scharl, Erik Wilde
Venue: WWW
Year: 2008

The World Wide Web has become the world's largest networked information resource, but references to geographical locations remain unstructured and typically implicit in nature. This lack of explicit spatial knowledge within the Web makes it difficult to service user needs for location-specific information. At present, spatial knowledge is hidden in many small information fragments such as addresses on Web pages, annotated photos with GPS co-ordinates, geographic mapping applications, and geotags in user-generated content. Several emerging formats that primarily or secondarily include location metadata, like GeoRSS, KML, and microformats, aim to improve this state of affairs. However, the question remains how to extract, index, mine, find, view, mashup, and exploit Web content using its location semantics. This work-shop brings together researchers from academia and industry labs to discuss and present the latest results and trends in all facets of the relationships between location concepts and Web information.
iRobot: an intelligent crawler for web forums
Authors: Rui Cai, Jiang-Ming Yang, Wei Lai, Yida Wang, Lei Zhang
Venue: WWW
Year: 2008

We study in this paper the Web forum crawling problem, which is a very fundamental step in many Web applications, such as search engine and Web data mining. As a typical user-created content (UCC), Web forum has become an important resource on the Web due to its rich information contributed by millions of Internet users every day. However, Web forum crawling is not a trivial problem due to the in-depth link structures, the large amount of duplicate pages, as well as many invalid pages caused by login failure issues. In this paper, we propose and build a prototype of an intelligent forum crawler, iRobot, which has intelligence to understand the content and the structure of a forum site, and then decide how to choose traversal paths among different kinds of pages. To do this, we first randomly sample (download) a few pages from the target forum site, and introduce the page content layout as the characteristics to group those pre-sampled pages and re-construct the forum's sitemap. After that, we select an optimal crawling path which only traverses informative pages and skips invalid and duplicate ones. The extensive experimental results on several forums show the performance of our system in the following aspects: 1) Effectiveness - Compared to a generic crawler, iRobot significantly decreases the duplicate and invalid pages; 2) Efficiency - With a small cost of pre-sampling a few pages for learning the necessary knowledge, iRobot saves substantial network bandwidth and storage as it only fetches informative pages from a forum site; and 3) Long threads that are divided into multiple pages can be re-concatenated and archived as a whole thread, which is of great help for further indexing and data mining.
Fourth international workshop on adversarial information retrieval on the web (AIRWeb 2008)
Authors: Carlos Castillo, Kumar Chellapilla, Dennis Fetterly
Venue: WWW
Year: 2008

Adversarial IR in general, and search engine spam, in particular, are engaging research topics with a real-world impact for Web users, advertisers and publishers. The AIRWeb workshop will bring researchers and practitioners in these areas together, to present and discuss state-of-the-art techniques as well as real-world experiences. Given the continued growth in search engine spam creation and detection efforts, we expect interest in this AIRWeb to surpass that of the previous three editions of the workshop (held jointly with WWW 2005, SIGIR 2006, and WWW 2007 respectively).
A graph-theoretic approach to webpage segmentation
Authors: Deepayan Chakrabarti, Ravi Kumar, Kunal Punera
Venue: WWW
Year: 2008

We consider the problem of segmenting a webpage into visually and semantically cohesive pieces. Our approach is based on formulating an appropriate optimization problem on weighted graphs, where the weights capture if two nodes in the DOM tree should be placed together or apart in the segmentation; we present a learning framework to learn these weights from manually labeled data in a principled manner. Our work is a significant departure from previous heuristic and rule-based solutions to the segmentation problem. The results of our empirical analysis bring out interesting aspects of our framework, including variants of the optimization problem and the role of learning.
Action science approach to nonprofit housing services using web 2.0 mapping tools
Authors: Yao-Jen Chang, Hsin-Yu Hsu, Tsen-Yung Wang
Venue: WWW
Year: 2008

The study follows action science approach to the problem of nonprofit housing services. After 4 months of action sciencebased activities, such as organized participant observations, indepth interviews, field work, and focus group studies, the main findings are (1) Web 2.0 suits nonprofit organizations better than traditional webs in terms of maintenance cost and usability, (2) mapping tools make better GUI with respect to web-based housing services, and (3) context-aware personalization can translate to better user experiences as an RDFS-based working prototype has been built and tested. A user survey shows high level user satisfaction. Although the case study was carried in a nonprofit housing organization, the practices in action research approach can be applied to other NPOs as well.
Rich media and web 2.0
Authors: Edward Y. Chang, Ken Ong, Susanne Boll, Wei-Ying Ma
Venue: WWW
Year: 2008

Rich media data, such as video, imagery, music, and gaming, do no longer play just a supporting role on the World Wide Web to text data. Thanks to Web 2.0, rich media is the primary content on sites such as Flickr, PicasaWeb, YouTube, and QQ. Because of massive user generated content, the volume of rich media being transmitted on the Internet has surpassed that of text. It is vital to properly manage these data to ensure efficient bandwidth utilization, to support effective indexing and search, and to safeguard copyrights (just to name a few). This panel invites both researchers and practitioners to discuss the challenges of Web-scale media-data management. In particular, the panelists will address issues such as leveraging Rich Media and Web 2.0, indexing, search, and scalability.
Report on semantic web for health care and life sciences workshop
Authors: Huajun Chen, Kei-Hoi Cheung, Michel Dumontier, Eric Prud&apos, hommeaux, Alan Ruttenberg, Susie Stephens, Yimin Wang
Venue: WWW
Year: 2008

The Semantic Web for Health Care and Life Sciences Workshop will be held in Beijing, China, on April 22, 2008. The goal of the workshop is to foster the development and advancement in the use of Semantic Web technologies to facilitate collaboration, research and development, and innovation adoption in the domains of Health Care and Life Sciences, We also encourage the participation of all research communities in this event, with enhanced participation from Asia due to the location of the event. The workshop consists of two invited keynote talks, eight peer-reviewed presentations, and one panel discussion.
Finding core members in virtual communities
Authors: Haiqiang Chen, Xueqi Cheng, Yue Liu
Venue: WWW
Year: 2008

Finding the core members of a virtual community is an important problem in community analysis. Here we presented an simulated annealing algorithm to solve this problem by optimizing the user interests concentration ratio in user groups. As an example, we test this algorithm on a virtual community site and evaluate its results using human "gold standard" method.
Using subspace analysis for event detection from web click-through data
Authors: Ling Chen, Yiqun Hu, Wolfgang Nejdl
Venue: WWW
Year: 2008

Although most of existing research usually detects events by analyzing the content or structural information of Web documents, a recent direction is to study the usage data. In this paper, we focus on detecting events from Web click-through data generated by Web search engines. We propose a novel approach which effectively detects events from click-through data based on robust subspace analysis. We first transform click-through data to the 2D polar space. Next, an algorithm based on Generalized Principal Component Analysis (GPCA) is used to estimate subspaces of transformed data such that each subspace contains query sessions of similar topics. Then, we prune uninteresting subspaces which do not contain query sessions corresponding to real events by considering both the semantic certainty and the temporal certainty of query sessions in each subspace. Finally, various events are detected from interesting subspaces by utilizing a nonparametric clustering technique. Compared with existing approaches, our experimental results based on real-life click-through data have shown that the proposed approach is more accurate in detecting real events and more effective in determining the number of events.
Efficient multi-keyword search over p2p web
Authors: Hanhua Chen, Hai Jin, Jiliang Wang, Lei Chen, Yunhao Liu, Lionel M. Ni
Venue: WWW
Year: 2008

Current search mechanisms of DHT-based P2P systems can well handle a single keyword search problem. Other than single keyword search, multi-keyword search is quite popular and useful in many real applications. Simply using the solution for single keyword search will require distributed intersection/union operations in wide area networks, leading to unacceptable traffic cost. As it is well known that Bloom Filter (BF) is effective in reducing traffic, we would like to use BF encoding to handle multi-keyword search. Applying BF is not difficult, but how to get optimal results is not trivial. In this study we show, through mathematical proof, that the optimal setting of BF in terms of traffic cost is determined by the global statistical information of keywords, not the minimized false positive rate as claimed by previous methods. Through extensive experiments, we demonstrate how to obtain optimal settings. We further argue that the intersection order between sets is important for multi-keyword search. Thus, we design optimal order strategies based on BF for both "and" and "or" queries. To better evaluate the performance of this design, we conduct extensive simulations on TREC WT10G test collection and the query log of a commercial search engine. Results show that our design significantly reduces the search traffic of existing approach by 73%.
Context-based page unit recommendation for web-basedsensemaking tasks
Authors: Wen-Huang Cheng, David Gotz
Venue: WWW
Year: 2008

Sensemaking tasks require users to perform complex research behaviors to gather and comprehend information from many sources. Such tasks are common and include, for example, researching vacation destinations or deciding how to invest. In this paper, we present an algorithm and interface that provides context-based page unit recommendation to assist in connection discovery during sensemaking tasks. We exploit the natural note-taking activity common to sensemaking behavior as the basis for a task-specific context model. Each web page visited by a user is dynamically analyzed to determine the most relevant content fragments which are then recommended to the user. Our initial evaluations indicate that our approach improves user performance.
Model bloggers' interests based on forgetting mechanism
Authors: Yuan Cheng, Guang Qiu, Jiajun Bu, Kangmiao Liu, Ye Han, Can Wang, Chun Chen
Venue: WWW
Year: 2008

Blogs have been expanded at an incredible speed in recent years. Plentiful personal information makes blogs a popular way mining user profiles. In this paper, we propose a novel bloggers' interests modeling approach based on forgetting mechanism. A new forgetting function is introduced to track interest drift. Based on that, the Short Term Interest Models (STIM) and Long Term Interest Models (LTIM) are constructed to describe bloggers' short-term and long-term interests. The experiments show that both models can identify bloggers' preferences well respectively.
How people use the web on mobile devices
Authors: Yanqing Cui, Virpi Roto
Venue: WWW
Year: 2008

This paper describes a series of user studies on how people use the Web via mobile devices. The data primarily comes from contextual inquiries with 47 participants between 2004 and 2007, and is complemented with a phone log analysis of 577 panelists in 2007. We report four key contextual factors in using the Web on mobile devices and propose mobile Web activity taxonomy. The framework contains three user activity categories identical to previous stationary Web studies: information seeking, communication, and transaction, and a new category: personal space extension. The new category refers to the practice that people put their content on the Web for personal access, therefore extending their personal information space.
Composite process oriented service discovery in preserving business and timed relation
Authors: Yu Dai, Lei Yang, Bin Zhang, Kening Gao
Venue: WWW
Year: 2008

This paper proposes an approach for solving the problem of composite process oriented service discovery with preserving business and timed relation. Key to our approach is the definition of requirement towards service. Such requirement not only constrains the functional semantics on an operation of service, but also constrains the timed and business relation among operations of service. Thus, services fulfilling such requirement can preserve the business and timed relation of the composite process. In order to automatically discover satisfied services, a multilevel matching relation model is defined which includes matching rules on the level of syntactic, functional semantics and behavioral semantics to test whether service is similar to the requirement. And based on such relation model, an algorithm for discovering services for the composite process is proposed. The experimentation shows that the proposed approach can preserve the timed and business relation effectively.
Feature weighting in content based recommendation system using social network analysis
Authors: Souvik Debnath, Niloy Ganguly, Pabitra Mitra
Venue: WWW
Year: 2008

We propose a hybridization of collaborative filtering and content based recommendation system. Attributes used for content based recommendations are assigned weights depending on their importance to users. The weight values are estimated from a set of linear regression equations obtained from a social network graph which captures human judgment about similarity of items.
Representing a web page as sets of named entities of multiple types: a model and some preliminary applications
Authors: Nan Di, Conglei Yao, Mengcheng Duan, Jonathan J. H. Zhu, Xiaoming Li
Venue: WWW
Year: 2008

As opposed to representing a document as a "bag of words" in most information retrieval applications, we propose a model of representing a web page as sets of named entities of multiple types. Specifically, four types of named entities are extracted, namely person, geographic location, organization, and time. Moreover, the relations among these entities are also extracted, weighted, classified and marked by labels. On top of this model, some interesting applications are demonstrated. In particular, we introduce a notion of person-activity, which contains four different elements: person, location, time and activity. With this notion and based on a reasonably large set of web pages, we are able to show how one person's activities can be attributed by time and location, which gives a good idea of the mobility of the person under question.
Layman tuning of websites: facing change resilience
Authors: Oscar Díaz, Cristóbal Arellano, Jon Iturrioz
Venue: WWW
Year: 2008

Client scripting permits end users to customize content, layout or style of their favourite websites. But current scripting suffers from a tight coupling with the website. If the page changes, all the scripting can fall apart. The problem is that websites are reckoned to evolve frequently, and this can jeopardize all the scripting efforts. To avoid this situation, this work enriches websites with a "modding interface" in an attempt to decouple layman's script from website upgrades. From the website viewpoint, this interface ensures safe scripting, i.e. scripts that do not break the page. From a scripter perspective, this interface limits tuning but increases change resilience. The approach tries to find a balance between openness (scripter free inspection) and modularity (scripter isolation from website design decisions) that permits scripting to scale up as a mature software practice. The approach is realized for Greasemonkey scripts.
Towards context-aware semantic web service discovery through conceptual situation spaces
Authors: Stefan Dietze, Alessio Gugliotta, John Domingue
Venue: WWW
Year: 2008

Context-awareness is highly desired across several application domains. Semantic Web Services (SWS) enable the automatic discovery of distributed Web services based on comprehensive semantic representations. However, although SWS technology supports the automatic allocation of resources for a given well-defined task, it does not entail the discovery of appropriate SWS representations for a given situational context. Whereas tasks are highly dependent on the situational context in which they occur, SWS technology does not explicitly encourage the representation of domain situations. Moreover, describing the complex notion of a specific situation in all its facets is a costly task and may never reach semantic completeness. Particularly, following the symbolic SWS approach leads to ambiguity issues and does not entail semantic meaningfulness. Apart from that, not any real-world situation completely equals another, but has to be matched to a finite set of semantically defined parameter descriptions to enable context-adaptability. To overcome these issues, we propose Conceptual Situation Spaces (CSS) which are aligned to established SWS standards. CSS enable the description of situation characteristics as members in geometrical vector spaces following the idea of Conceptual Spaces. Semantic similarity between situations is calculated in terms of their Euclidean distance within a CSS. Extending merely symbolic SWS descriptions with context information on a conceptual level through CSS enables similarity-based matchmaking between real-world situation characteristics and predefined resource representations as part of SWS descriptions. To prove the feasibility, we apply our approach to the domain of E-Learning and provide a proof-of-concept prototype.
Using graphics processors for high-performance IR query processing
Authors: Shuai Ding, Jinru He, Hao Yan, Torsten Suel
Venue: WWW
Year: 2008

Web search engines are facing formidable performance challenges as they need to process thousands of queries per second over billions of documents. To deal with this heavy workload, current engines use massively parallel architectures of thousands of machines that require large hardware investments.
An initial investigation on evaluating semantic web instance data
Authors: Li Ding, Jiao Tao, Deborah L. McGuinness
Venue: WWW
Year: 2008

Many emerging semantic web applications include ontologies from one set of authors and instance data from another (often much larger) set of authors. Often ontologies are reused and instance data is integrated in manners unanticipated by their authors. Not surprisingly, many instance data rich applications encounter instance data that is not compatible with the expectations of the original ontology author(s). This line of work focuses on issues related to semantic expectation mismatches in instance data. Our initial results include a customizable and extensible service-oriented evaluation architecture, and a domain implementation called PmlValidator, which checks instance data using the corresponding ontologies and additional style requirements.
As we may perceive: finding the boundaries of compound documents on the web
Authors: Pavel Dmitriev
Venue: WWW
Year: 2008

This paper considers the problem of identifying on the Web compound documents (cDocs) -- groups of web pages that in aggregate constitute semantically coherent information entities. Examples of cDocs are a news article consisting of several html pages, or a set of pages describing specifications, price, and reviews of a digital camera. Being able to identify cDocs would be useful in many applications including web and intranet search, user navigation, automated collection generation, and information extraction.In the past, several heuristic approaches have been proposed to identify cDocs [1][5]. However, heuristics fail to capture the variety of types, styles and goals of information on the web, and do not account for the fact that the definition of a cDoc often depends on the context. This paper presents an experimental evaluation of three machine learning-based algorithms for cDoc discovery. These algorithms are responsive to the varying structure of cDocs and adaptive to their application-specific nature. Based on our previous work [4], this paper proposes a different scenario for discovering cDocs, and compares in this new setting the local machine learned clustering algorithm from [4] to a global purely graph based approach [3] and a Conditional Markov Network approach previously applied to noun coreference task [6]. The results show that the approach of [4] outperforms the other algorithms, suggesting that global relational characteristics of web sites are too noisy for cDoc identification purposes.