OpenRaiser/Intern-Atlas huggingface dataset:
Web-scale entity-relation search architecture
Authors: Soumen Chakrabarti, Devshree Sane, Ganesh Ramakrishnan
Venue: WWW
Year: 2011

Enabling entity search and ranking at Web-scale is fraught with many challenges: annotating the corpus with entities and types, query language design, index design, query processing logic, and answer consolidation. We describe a Webscale entity search engine we are building to handle over a billion Web pages, over 200,000 types, over 1,500,000 entities, and hundreds of entity annotations per page. We describe the design of compressed, token span oriented indices for entity and type annotations. Our prototype demonstrates the practicality of Web-scale entity-relation search. Categories and Subject Descriptors: H.3.3 [Information Search and Retrieval]: Search process,
Location specific summarization of climatic and agricultural trends
Authors: Sunandan Chakraborty, Lakshminarayanan Subramanian
Venue: WWW
Year: 2011

Climate change can directly impact agriculture. Failure in different aspects of agriculture due to climate change and other influencing factors, are extremely rampant in several agrarian economies, most of which go unnoticed. In this paper, we describe the design of a system that mines disparate information sources on the Web to automatically summarize important climatic and agricultural trends for any specific location and construct a location-specific climatic and agricultural information portal. We have evaluated the system across 605 different districts in India. The results revealed a pan-India scenario of different problem affected areas. The key findings from this work include, around 64.58% of the districts of India suffer from soil related issues and 76.02% have water related problems. We have also manually validated the authenticity of our information sources and validated our summarized results for specific locations with findings in reputed journals and authoritative sources.
Learning facial attributes by crowdsourcing in social media
Authors: Yan-Ying Chen, Winston H. Hsu, Hong-Yuan Mark Liao
Venue: WWW
Year: 2011

Facial attributes such as gender, race, age, hair style, etc., carry rich information for locating designated persons and profiling the communities from image/video collections (e.g., surveillance videos or photo albums). For plentiful facial attributes in photos and videos, collecting costly manual annotations for training detectors is time-consuming. We propose an automatic facial attribute detection method by exploiting the great amount of weakly labelled photos in social media. Our work can (1) automatically extract training images from the semantic-consistent user groups and (2) filter out noisy training photos by multiple mid-level features (by voting). Moreover, we introduce a method to harvest less-biased negative data for preventing uneven distribution of certain attributes. The experiments show that our approach can automatically acquire training photos for facial attributes and is on par with that by manual annotations.
Analyzing and accelerating web access in a school in peri-urban India
Authors: Jay Chen, David Hutchful, William Thies, Lakshminarayanan Subramanian
Venue: WWW
Year: 2011

While computers and Internet access have growing penetration amongst schools in the developing world, intermittent connectivity and limited bandwidth often prevent them from being fully utilized by students and teachers. In this paper, we make two contributions to help address this problem. First, we characterize six weeks of HTTP traffic from a primary school outside of Bangalore, India, illuminating opportunities and constraints for improving performance in such settings. Second, we deploy an aggressive caching and prefetching engine and show that it accelerates a user's overall browsing experience (apart from video content) by 2.8x. Our accelerator leverages innovative techniques that have been proposed, but not evaluated in detail, including the effectiveness of serving stale pages, cached page highlighting, and client-side prefetching. Unlike proxy-based techniques, our system is bundled as an open-source Firefox plugin and runs directly on client machines. This allows easy installation and configuration by end users, which is especially important in developing regions where a lack of permissions or technical expertise often prevents modification of internal network settings.
Design and implementation of contextual information portals
Authors: Jay Chen, Russell Power, Lakshminarayanan Subramanian, Jonathan Ledlie
Venue: WWW
Year: 2011

This paper presents a system for enabling offline web use to satisfy the information needs of disconnected communities. We describe the design, implementation, evaluation, and pilot deployment of an automated mechanism to construct Contextual Information Portals (CIPs). CIPs are large searchable information repositories of web pages tailored to the information needs of a target population. We combine an efficient classifier with a focused crawler to gather the web pages for the portal for any given topic. Given a set of topics of interest, our system constructs a CIP containing the most relevant pages from the web across these topics. Using several secondary school course syllabi, we demonstrate the effectiveness of our system for constructing CIPs for use as an education resource. We evaluate our system across several metrics: classification accuracy, crawl scalability, crawl accuracy and harvest rate. We describe the utility and usability of our system based on a preliminary deployment study at an after-school program in India, and also outline our ongoing larger-scale pilot deployment at five schools in Kenya.
Survivability-oriented self-tuning of web systems
Authors: Bihuan Chen, Xin Peng, Yijun Yu, Wenyun Zhao
Venue: WWW
Year: 2011

Running in a highly uncertain and changing environment, Web systems cannot always provide full set of services with optim¬al quality, especially when the workload is high or failures in subsys-tems occur frequently. It is thus desirable to continuously maintain a high satisfaction level of the system value proposition, hereafter survivability assurance, while relaxing/sacrificing certain quality/functional requirements that are not crucial to the survival of the Web systems. In this paper, we propose a requirements-driven self-tuning method for survivability assurance of Web systems. Using a value-based feedback controller plus a requirements-oriented reasoner, our method makes both quality and functional requirements tradeoffs decisions at runtime.
Generating summaries for ontology search
Authors: Gong Cheng, Weiyi Ge, Yuzhong Qu
Venue: WWW
Year: 2011

This poster proposes a novel approach for generating summaries for ontology search. Following previous work, we define ontology summarization as the problem of ranking and selecting RDF sentences, for which we examine three aspects. Firstly, to assess the salience of RDF sentences in an ontology, we devise a bipartite graph model for representing the ontology and analyze random walks on this graph. Secondly, to reflect how an ontology is matched with user needs expressed via keyword queries, we incorporate query relevance into the selection of RDF sentences. Finally, to improve the unity of a summary, we optimize its cohesion in terms of the connections between constituent RDF sentences. We have implemented an online prototype system called Falcons Ontology Search.
Addressing people's information needs directly in a web search result page
Authors: Lydia B. Chilton, Jaime Teevan
Venue: WWW
Year: 2011

Web search engines have historically focused on connecting people with information resources. For example, if a person wanted to know when their flight to Hyderabad was leaving, a search engine might connect them with the airline where they could find flight status information. However, search engines have recently begun to try to meet people's search needs directly, providing, for example, flight status information in response to queries that include an airline and a flight number. In this paper, we use large scale query log analysis to explore the challenges a search engine faces when trying to meet an information need directly in the search result page. We look at how people's interaction behavior changes when inline content is returned, finding that such content can cannibalize clicks from the algorithmic results. We see that in the absence of interaction behavior, an individual's repeat search behavior can be useful in understanding the content's value. We also discuss some of the ways user behavior can be used to provide insight into when inline answers might better trigger and what types of additional information might be included in the results.
Enhancing web search with entity intent
Authors: Na Dai, Xiaoguang Qi, Brian D. Davison
Venue: WWW
Year: 2011

Web entities, such as documents and hyperlinks, are created for different purposes, or intents. Existing intent-based retrieval methods largely focus on information seekers' intent expressed by queries, ignoring the other side of the problem: web content creators' intent. We argue that understanding why the content was created is also important. In this work, we propose to classify such intents into two broad categories: "navigational" and "informational". Then we incorporate such intents into traditional retrieval models, and show their effect on ranking performance.
Filtering microblogging messages for social TV
Authors: Ovidiu Dan, Junlan Feng, Brian D. Davison
Venue: WWW
Year: 2011

Social TV was named one of the ten most important emerging technologies in 2010 by the MIT Technology Review. Manufacturers of set-top boxes and televisions have recently started to integrate access to social networks into their products. Some of these systems allow users to read microblogging messages related to the TV program they are currently watching. However, such systems suffer from low precision and recall when they use the title of the show as keywords when retrieving messages, without any additional filtering.
Analysis and tracking of emotions in english and bengali texts: a computational approach
Authors: Dipankar Das
Venue: WWW
Year: 2011

The present discussion highlights the aspects of an ongoing doctoral thesis grounded on the analysis and tracking of emotions from English and Bengali texts. Development of lexical resources and corpora meets the preliminary urgencies. The research spectrum aims to identify the evaluative emotional expressions at word, phrase, sentence, and document level granularities along with their associated holders and topics. Tracking of emotions based on topic or event was carried out by employing sense based affect scoring techniques. The labeled emotion corpora are being prepared from unlabeled examples to cope with the scarcity of emotional resources, especially for the resource constraint language like Bengali. Different unsupervised, supervised and semi-supervised strategies, adopted for coloring each outline of the research spectrum produce satisfactory outcomes
T-RecS: team recommendation system through expertise and cohesiveness
Authors: Anwitaman Datta, Jackson Tan Teck Yong, Anthony Ventresque
Venue: WWW
Year: 2011

Searching for people by exploration of social networks structure is an interesting problem which has recently gathered a lot of attention. Expert recommendation is an important but also extensively researched problem. In contrast, the generalized problem of team recommendation has not been studied a lot. The purpose of this demo is to show a multidisciplinary team search and recommendation prototype. While the current demo uses specific (NTU academic) data-set, the framework is generic, and can be extended for other domains subject to availability of suitable information.
Computational advertising: leveraging user interaction & contextual factors for improved ad retrieval & ranking
Authors: Kushal S. Dave
Venue: WWW
Year: 2011

Computational advertising, popularly known as Online advertising or Web advertising, refers to finding the most relevant ads matching a particular context on the web. It is a scientific sub-discipline at the intersection of information retrieval, statistical modeling, machine learning, optimization, large scale search and text analysis. The core problem attacked in computational advertising (CA) is of the match making between the ads and the context. Based on the context, CA can be broadly compartmentalized into following three areas: Sponsored search, Contextual advertising and Social advertising. Sponsored search refers to the placement of ads on search results page. Contextual advertising deals with matching advertisements to the third party web pages. We refer the placements of ads on a social networking page, leveraging user's social contacts as social advertising. My research work aims at leveraging various user interactions, ad and advertiser related information and contextual information for these three areas of advertising. The research work focuses on the identification of various factors that contribute in retrieving and ranking the most relevant set of ads that match best with the context. Specifically, information associated with the user, publisher and advertiser is leveraged for this purpose.
Second international workshop on web science and information exchange in the medical web (MedEx 2011)
Authors: Kerstin Denecke, Peter Dolog
Venue: WWW
Year: 2011

The amount of Social Media Data dealing with medical and health issues increased significantly in the last couple of years. Medical Social Media Data now provides a new source of information within information gaining contexts. Facts, experiences, opinions or information on behavior can be found in the Medicine or Health 2.0 and could support a broad range of applications. This workshop is devoted to the technologies for dealing with social- and multi media for medical information gathering and exchange. This specific data and the processes of information gathering poses many challenges given the increasing content on the Web and the trade off of filtering noise at the cost of losing information which is potentially relevant.
Efficient k-nearest neighbor graph construction for generic similarity measures
Authors: Wei Dong, Moses Charikar, Kai Li
Venue: WWW
Year: 2011

K-Nearest Neighbor Graph (K-NNG) construction is an important operation with many web related applications, including collaborative filtering, similarity search, and many others in data mining and machine learning. Existing methods for K-NNG construction either do not scale, or are specific to certain similarity measures. We present NN-Descent, a simple yet efficient algorithm for approximate K-NNG construction with arbitrary similarity measures. Our method is based on local search, has minimal space overhead and does not rely on any shared global index. Hence, it is especially suitable for large-scale applications where data structures need to be distributed over the network. We have shown with a variety of datasets and similarity measures that the proposed method typically converges to above 90% recall with each point comparing only to several percent of the whole dataset on average.
Query completion without query logs for song search
Authors: Nitin Dua, Kanika Gupta, Monojit Choudhury, Kalika Bali
Venue: WWW
Year: 2011

We describe a new method for query completion for Bollywood song search without using query logs. Since song titles in non-English languages (Hindi in our case) are mostly present as Roman transliterations of the native script, both the queries and documents have a large number of valid variations. We address this problem by using a Roman to Hindi transliteration engine coupled with appropriate ranking and implementation strategies. Out of 100 test cases, our system could generate the correct suggestion for 91 queries.
Online spelling correction for query completion
Authors: Huizhong Duan, Bo-June Paul Hsu
Venue: WWW
Year: 2011

In this paper, we study the problem of online spelling correction for query completions. Misspelling is a common phenomenon among search engines queries. In order to help users effectively express their information needs, mechanisms for automatically correcting misspelled queries are required. Online spelling correction aims to provide spell corrected completion suggestions as a query is incrementally entered. As latency is crucial to the utility of the suggestions, such an algorithm needs to be not only accurate, but also efficient.
Accelerating instant question search with database techniques
Authors: Takeharu Eda, Toshio Uchiyama, Katsuji Bessho, Norifumi Katafuchi, Alice Chen, Ryoji Kataoka
Venue: WWW
Year: 2011

Distributed question answering services, like Yahoo Answer and Aardvark, are known to be useful for end users and have also opened up numerous topics ranging in many research fields. In this paper, we propose a user-support tool for composing questions in such services. Our system incrementally recommends similar questions while users are typing their question in a sentence, which gives the users opportunities to know that there are similar questions that have already been solved. A question database is semantically analyzed and searched in the semantic space by boosting the performance of similarity searches with database techniques such as server/client caching and LSH (Locality Sensitive Hashing). The more text the user enters, the more similar the recommendations will become to the ultimately desired question. This unconscious editing-as-a-sequence-of-searches approach helps users to form their question incrementally through interactive supplementary information. Not only askers nor repliers, but also service providers have advantages such as that the knowledge of the service will be autonomously refined by avoiding for novice users to repeat questions which have been already solved.
OntoWiki mobile: knowledge management in your pocket
Authors: Timofey Ermilov, Norman Heino, Sören Auer
Venue: WWW
Year: 2011

As comparatively powerful mobile computing devices become more common, mobile web applications have started gaining in popularity. Such mobile web applications as Google Mail or Calendar are already in everyday use of millions of people. Some first examples of these applications use Semantic Web technologies and information in the form of RDF (e.g. TripIt). An important feature of these applications is their ability to provide offline functionality with local updates for later synchronization with a web server. The key problem to this is the reconciliation, i.e. the problem of potentially conflicting updates from disconnected clients. In this paper we present an approach for a mobile semantic collaboration platform based on the OntoWiki framework [1]. It allows users to collect instance data and refine the structure knowledge bases on the go. A crucial part of OntoWiki Mobile is the advanced conflict resolution for RDF stores. The approach is based on the EvoPat [2] method for data evolution and ontology refactoring.
Speech and multimodal interaction in mobile search
Authors: Junlan Feng, Michael Johnston, Srinivas Bangalore
Venue: WWW
Year: 2011

This tutorial highlights the characteristics of mobile search comparing with its desktop counterpart, reviews the state of art technologies of speech-based mobile search, and presents opportunities for exploiting multimodal interaction to optimize the efficiency of mobile search. It is suitable for students, researchers and practitioners working in the areas of spoken language processing, multimodal and search with an emphasis on a synergistic integration of these technologies for applications on mobile devices. We will provide detailed bibliography and sufficient literature for everyone interested to jumpstart work on this topic
The web of things
Authors: Carolina Fortuna, Marko Grobelnik
Venue: WWW
Year: 2011

The Web, similar to other successful man made systems is continuously evolving. With the miniaturization and increased performance of computing devices which are also being embedded in common physical objects, it is natural that the Web evolved to also include these - therefore the Web of Things. This tutorial provides an overview of the system vertical structure by identifying the relevant components, illustrating their functionality and showing existing tools and systems. The aim is to show how small devices can be connected to the Web at various levels of abstraction and transform them into "first-class" Web residents.
CoSi: context-sensitive keyword query interpretation on RDF databases
Authors: Haizhou Fu, Sidan Gao, Kemafor Anyanwu
Venue: WWW
Year: 2011

The demo will present CoSi, a system that enables context-sensitive interpretation of keyword queries on RDF databases. The techniques for representing, managing and exploiting query history are central to achieving this objective. The demonstration will show the effectiveness of our approach for capturing a user's querying context from their query history. Further, it will show how context is utilized to influence the interpretation of a new query. The demonstration is based on DBPedia, the RDF representation of Wikipedia.
HyLiEn: a hybrid approach to general list extraction on the web
Authors: Fabio Fumarola, Tim Weninger, Rick Barber, Donato Malerba, Jiawei Han
Venue: WWW
Year: 2011

We consider the problem of automatically extracting general lists from the web. Existing approaches are mostly dependent upon either the underlying HTML markup or the visual structure of the Web page. We present HyLiEn an unsupervised, Hybrid approach for automatic List discovery and Extraction on the Web. It employs general assumptions about the visual rendering of lists, and the structural representation of items contained in them. We show that our method significantly outperforms existing methods.
WonderWhat: real-time event determination from photos
Authors: Mingyan Gao, Xian-Sheng Hua, Ramesh C. Jain
Venue: WWW
Year: 2011

How often did you feel disappointed in a foreign country, when you had been craving for participating in authentic native events but miserably ended up with being lost in the crowd, due to ignorance of the local culture? Have you ever imagined that with merely a simple click, a tool can identify the events that are right in front of you? As a step in this direction, in this paper, we propose a system that provides users with information of the public events that they are attending by analyzing in real time their photos taken at the event, leveraging both spatio-temporal context and photo content. To fulfill the task, we designed the system to collect event information, maintain dedicated event database, build photo content model for event types, and rank the final results. Extensive experiments were conducted to prove the effectiveness of each component.
Ranking on large-scale graphs with rich metadata
Authors: Bin Gao, Taifeng Wang, Tie-Yan Liu
Venue: WWW
Year: 2011

For many Web applications, one needs to deal with the ranking problem on large-scale graphs with rich metadata. However, it is non-trivial to perform efficient and effective ranking on them. On one aspect, we need to design scalable algorithms. On another aspect, we also need to develop powerful computational infrastructure to support these algorithms. This tutorial aims at giving a timely introduction to the promising advances in the aforementioned aspects in recent years, and providing the audiences with a comprehensive view on the related literature.