Sigalit Ur

The shark-search algorithm. An application: tailored Web site mapping

Abstract This paper introduces the “shark search” algorithm, a refined version of one of the first dynamic Web search algorithms, the “fish search”. The shark-search has been embodied into a dynamic Web site mapping that enables users to tailor Web maps to their interests. Preliminary experiments show significant improvements over the original fish-search algorithm.

Mining expertise and interests from social media

The rising popularity of social media in the enterprise presents new opportunities for one of the organizations most important needs--expertise location. Social media data can be very useful for expertise mining due to the variety of existing applications, the rich metadata, and the diversity of user associations with content. In this work, we provide an extensive study that explores the use of social media to infer expertise within a large global organization. We examine eight different social media applications by evaluating the data they produce through a large user survey, with 670 enterprise social media users. We distinguish between two semantics that relate a user to a topic: expertise in the topic and interest in it and compare these two semantics across the different social media applications.

Adding support for dynamic and focused search with Fetuccino

Abstract This paper proposes two enhancements to existing search services over the Web. One enhancement is the addition of limited dynamic search around results provided by regular Web search services, in order to correct part of the discrepancy between the actual Web and its static image as stored in search repositories. The second enhancement is an experimental two-phase paradigm that allows the user to distinguish between a domain query and a focused query within the dynamically identified domain. We present Fetuccino, an extension of the Mapuccino system that implements these two enhancements. Fetuccino provides an enhanced user-interface for visualization of search results, including advanced graph layout, display of structural information and support for standards (such as XML). While Fetuccino has been implemented on top of existing search services, its features could easily be integrated into any search engine for better performance. A light version of Fetuccino is available on the Internet at http://www.ibm.com/java/fetuccino.

Do you want to know?: recommending strangers in the enterprise

Recent studies on people recommendation have focused on suggesting people the user already knows. In this work, we use social media behavioral data to recommend people the user is not likely to know, but nonetheless may be interested in. Our evaluation is based on an extensive user study with 516 participants within a large enterprise and includes both quantitative and qualitative results. We found that many employees valued the recommendations, even if only one or two of nine recommendations were interesting strangers. Based on these results, we discuss potential deployment routes and design implications for a stranger recommendation feature.

The chasms of CSCW: a citation graph analysis of the CSCW conference

The CSCW conference is celebrating its 20th birthday. This is a perfect time to analyze the coherence of the field, to examine whether it has a solid core or sub-communities, and to identify various patterns of its development. In this paper we analyze the structure of the CSCW conference using structural analysis of the citation graph of CSCW and related publications. We identify the conferences core and most prominent clusters. We also define a measure to identify chasm-papers, namely papers cited significantly more outside the conference than within, and analyze such papers.

Social networks and discovery in the enterprise (SaND)

Traditional information discovery methods are based on content: documents, terms, and the relationships between them. In Web 2.0, people come into play as they create documents and tags in many forms. Personalized search, social graphs, content and people recommendation, are some of the tasks that can take advantage of this newly formed ecosystem. The Social Networks and Discovery (SaND) platform is an aggregation tool for information discovery and analysis over social data gathered from Web 2.0 applications in the enterprise. It leverages complex relationships between content and people as surfaced through the social applications to unleash the value of information. Its integrated index supports combining content-based analysis and people-based analysis over a rich data foundation. Enterprise social data is easily modeled and ingested into SaND, and can be further combined with data from external social applications. This demo will present three main functions provided by SaND: Social search: SaND supports search over the social data using a unified approach [1] in which all system entities (documents, people, tags) are searchable and retrievable (See Figure 1). The search UI enables the searcher to get a wider view on the query topic through results from all entity types, while uncovering the relationships between the on-screen entities. Entity recommendation: SaND can be utilized to recommend people and content for the searcher (Figure 2 shows the “Do You Know” widget for people recommendation). People are recommended according to their “social similarity” relations with the searcher, e.g. organizational and friending ties, similar tagging activity and more. Similarly, content that is related to people that are “socially related” to the searcher is recommended as valuable interesting data. Personalization: Search results are personalized by considering the relations of retrieved entities with the searcher. Entities are ranked according to their relevance to the query as well as according to their relationship strength with the searcher.

Best faces forward: a large-scale study of people search in the enterprise

This paper presents Faces, an application built to enable effective people search in the enterprise. We take advantage of the popularity Faces has gained within a globally distributed enterprise to provide an extensive analysis of how and why people search is used within the organization. Our study is primarily based on an analysis of the Faces query log over a period of more than four months, with over a million queries and tens of thousands of users. The analysis results are presented across four dimensions: queries, users, clicks, and actions, and lay the foundation for further advancement and research on the topic.

Why do we ReachOut?: functions of a semi-persistent peer support tool

Collaboration plays a vital role in todays new business environment. Knowledge that resides within peoples heads has become an invaluable resource. Many formal tools, such as e-mail or teamrooms, have been introduced to support formal collaboration and have been studied extensively. However, support for informal communication is still in its infancy. Much work has been done to analyze the functions that informal communication plays in the workplace. Recently, several studies have evaluated the roles that instant messaging (IM) plays in similar settings. Research shows that in the workplace, IM is used primarily for work-related purposes and accelerates the completion of important business tasks. Clearly, new tools that combine both formal and informal interaction can bring organizations tremendous rewards. ReachOut is a tool for semi-persistent collaboration and peer support developed by the Collaboration Technologies Group at the IBM Haifa Research Lab. This paper studies the role ReachOut plays in the workplace. We analyzed the collaboration activity of the community of IBM Haifa Labs employees who used ReachOut for a period of two months. As a result, we summarize the important functions played by tools that bridge between formal and informal communication in a workplace-based community.

Why do we ReachOut?: functions of a semi-persistent peer support tool[18] (abstract only)

Collaboration plays a vital role in todays new business environment. Knowledge that resides within peoples heads has become an invaluable resource. Many formal tools, such as e-mail or teamrooms, have been introduced to support formal collaboration and have been studied extensively. However, support for informal communication is still in its infancy. Much work has been done to analyze the functions that informal communication plays in the workplace. Recently, several studies have evaluated the roles that instant messaging (IM) plays in similar settings. Research shows that in the workplace, IM is used primarily for work-related purposes and accelerates the completion of important business tasks. Clearly, new tools that combine both formal and informal interaction can bring organizations tremendous rewards. ReachOut is a tool for semi-persistent collaboration and peer support developed by the Collaboration Technologies Group at the IBM Haifa Research Lab. This paper studies the role ReachOut plays in the workplace. We analyzed the collaboration activity of the community of IBM Haifa Labs employees who used ReachOut for a period of two months. As a result, we summarize the important functions played by tools that bridge between formal and informal communication in a workplace-based community.