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... then attempts to automatically fulfill them using common Internet information resources. Given the requirements that it must observe several applications and that it must also use multiple Internet information resources, we have adopted a five-tiered architecture (see Figure 1). The user interacts with the sundry applications shown at the bottom of the diagram, and the information management application in the middle. ...
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... In the future, profiles could indicate user expectations in regards to search queries, for example whether search aims at finding information in regards to a product name, a manufacturer, a dealer, or a data sheet for a product. Also, the current search context of the user might be gathered from the documents found on the local computer [15,13,14,37]. Keywords might be automatically determined from the contents of desktop documents to indicate user interest. ...
The importance of information in today's society is still growing and information search has become an essential task in both the workplace and in private life. eSearch services provide access to the abundance of information available on the Internet by means of search engine technology. However, conventional search engines have certain limitations in dealing with the typical information overload problems. With the application of personalisation techniques search engine pro-viders aim at moderating some of the problems by providing users with informa-tion access individualised to their needs. The aim of this paper is twofold. Firstly, techniques for personalisation of eSearch services are introduced. Secondly, the results of an empirical study of the market for eSearch services are presented. Typical examples illustrate eSearch personalisation in practice, and the diffusion of techniques and implications for further research in the domain are discussed.
... Content-based relationships are not explicitly defined within documents, but can be identified by reconnaissance agent software that compares the content of a collection of documents, and marks document pairs whose content is similar enough to label the documents as "related". Such software, found in such systems as Watson [3], Margin Notes [14], PowerScout [11], Letizia [11] and Suitor [13] can help remind a user of related documents created or viewed in the past, or of related documents from the web to which the user has never been exposed. Our research addresses the shortcomings of conventional tools for navigating the personal web and expands on the concepts inherent in reconnaissance agents. ...
... Margin Notes [14], the successor to the Remembrance Agent, analyzes web documents as well as user documents, and it invokes searches based on sections of the document instead of the whole text. Watson [3] performs similar work on open MS-Word and Internet Explorer documents, and provided some advanced heuristics for finding the characteristic words in a document. PowerScout [14] uses both the words in the current document and user profile information to perform its automated searches. ...
... For instance, consider an agent that performs automated search query modification by adding terms from a user profile to search queries. This is slightly different than reconnaissance agents [3,13,14] that only use data from currently open documents in their automated searches, and similar to the PowerScout [11] system, which combines short-term goal-oriented data (from the open documents) with longer-term measures of a user's interests (profiles). A single user profile is probably too general for most multifaceted users, since most wear various "hats" during a day, e.g., in the morning David Wolber is a computer science teacher, and in the afternoon a literature buff. ...
Reconnaissance agents show context by displaying documents with similar content to the one(s) the user currently has open. Research paper search engines show context by displaying documents that cite or are cited by the currently open document(s). We present a tool that applies such ideas to the personal web, that is, the space rooted in user documents but tightly connected to web documents as well. The tool organizes the personal web with a single topic hierarchy based on direct links, instead of the traditional file, bookmark, and (hidden) direct link hierarchies. The tool allows a user to easily navigate through related user and web documents, no matter whether the documents are related by directory-document, bookmark-document, direct-link, or even similar content relationships.
... Reconnaissance agents [4,14,16,18] integrate editing and searching by providing a zero-click [14] interface for searches. These systems push related information to the user by automatically gathering keywords from the open document and sending them to a search engine. ...
... In terms of gathering content-related documents, WebTop is similar to existing systems. Some reconnaissance agents, such as the Remembrance Agent [18], only search the personal space for related documents, while others search only the web [4,14,16]. Some "seed" the search only from a page in a browser [14], while others are attentive to Word documents [4] and other desktop applications [16]. ...
... Some reconnaissance agents, such as the Remembrance Agent [18], only search the personal space for related documents, while others search only the web [4,14,16]. Some "seed" the search only from a page in a browser [14], while others are attentive to Word documents [4] and other desktop applications [16]. WebTop currently is attentive to HTML documents being edited, Word documents, and web pages being browsed, and it searches both the personal space, the WWW, and the intersection (from the personal web to n degrees of separation). ...
This paper describes the nature of the modern personal information space (the personal web) and a tool that improves on conventional file management for organizing and exploring that space. Our premise is that a user's web experience should be as personal as possible, flowing easily between user and web documents, following various types of document relationship "links", and involving searches that take into account who is doing the searching.
... In particular, the Adaptive Web Site Agent will make recommendations based upon similarity between pages at a site and the analysis of web logs at the site. Adaptive Web Site Agent also shares some goals with the Remembrance Agent [18] and Watson [4]. Both of those systems recommend other information sources related to the current document focus of the user. ...
We discuss the design and evaluation of a class of agents that we call adaptive web site agents. The goal of such an agent is to help a user find additional information at a particular web site, adapting its behavior in response to the actions of the individual user and the actions of other visitors to the web site. The agent recommends related documents to visitors and we show that these recommendations result in increased information read at the site. It integrates and coordinates among different reasons for making recommendations including user preference for subject area, similarity between documents, frequency of citation, frequency of access, and patterns of access by visitors to the web site. We argue that this information is best used not to change the structure or content of the web site but rather to change the behavior of an animated agent that assists the user.
... Northwestern University's Watson [1] also uses tracking user behavior and automatically generated queries to a search engine to recommend pages-as does Powerscout. In addition, Watson has other interesting capabilities, such as searching for pictures or searching for contrasting information instead of that most similar. ...
This article reports on a new agent technology that helps Internet surfers to scout out the online terrain and recommend the best paths for the user to follow. These agents are called reconnaissance agents, programs that look ahead in the user's browsing activities and act as an advance scout to save the user needless searching and recommend the best paths to follow. Reconnaissance agents are also among the first representatives of a new class of computer applications, learning agents that infer user preferences and interests by tracking interactions between the user and the machine over the long term. Two examples of reconnaissance agents are provided in the article are that of Letizia and PowerScout. The main difference is that Letizia uses local reconnaissance, searching the neighborhood of the current page, while Powerscout uses global reconnaissance, making use of a traditional search engine to search the Web in general. Both the Letizia and the PowerScout style of agent have their advantages and disadvantages. This new technology permits users to maintain a focus on their quest for information while decreasing the time and frustration of finding material of interest.
... Northwestern University's Watson [2] also uses tracking user behavior and automatically generated queries to a search engine to recommend pages, as does Powerscout, and also has some other interesting capabilities, such as searching for pictures or searching for contrasting information instead of that most similar. ...
... PIMA is a client-side, content-based recommender system that monitors a user's actions in an application environment such as MS Word and suggests relevant resources from the Web to aid the user in their current task [4]. As the user works the PIMA client builds a summary of the current page using standard content-based information retrieval techniques. ...
. As it stands the Internet's "one size fits all" approach to information retrieval presents the average user with a serious information overload problem. Adaptive hypermedia systems can provide a solution to this problem by learning about the implicit and explicit preferences of individual users and using this information to personalise information retrieval processes. We describe and evaluate a two-stage personalised information retrieval system that combines a server-side similarity-based retrieval component with a client-side case-based personalisation component. We argue that this combination has a number of benefits in terms of personalisation accuracy, computational cost, flexibility, security and privacy. 1 Introduction The Internet currently consists of approximately 800 million pages of information across more than 8 million web sites, and there are over 200 million regular users from all walks of life with varying degrees of computer literacy and a wide range of i...
... Just-in-time information agents are systems that observe user behavior in everyday applications (e.g., word processors, WWW browsers, electronic mail systems), and build queries to distributed information repositories in order to provide a user with immediate access to relevant information. Efforts in building such systems have varied in the kind of document collections and applications used, the level of user modeling involved, the amount of user intervention, and the interface for presentation (Lieberman 1995, Rhodes and Starner 1996, Badue, Vaz, and Albuquerque 1998, Budzik et al. 1998, Kulyukin 1999, Budzik and Hammond 2000, Rhodes 2000, Maglio 2000. ...
... Our work on Information Management Assistants (Budzik et al. 1998, Budzik and has focused on modeling user behavior in everyday productivity applications to make decisions about when to retrieve relevant information, and what kind of information would be useful to the task at hand. We have built a prototype system, Watson, which observes user behavior in Microsoft Word (a word processor) and Microsoft Internet Explorer (a WWW browser) in order to decide when and from where to retrieve related information. ...
Agents that provide just-in-time access to relevant online material by observing user behavior in everyday applications have been the focus of much research, both in our lab, and elsewhere. These systems analyze information objects the user is manipulating in order to recommend additional information. Designers of such systems typically make the assumption that objects similar to the one being manipulated by the user will be useful to her. Our own experiments show that users do find many of the documents retrieved by a system of this type are relevant. Yet in the context of a specific task, users find fewer of these documents are useful. Our main point is that in order to make just-in-time information systems truly useful, we need to reexamine the "similarity assumption" inherent in many of these systems' designs. In light of this, we propose techniques that bring modest amounts of task-specific knowledge to bear in order to perform lexical transformations on the queri...
... Our work on Information Management Assistants (IMAs) [6, 8] is strongly motivated by the avenues the above approaches leave unexplored, and by what is known about the behavior of users in information systems. ...
... A preliminary version of this architecture is realized in Watson, the first IMA we have built [6, 8]. Watson has several application adapters, which are used to gain access to an application's internal representation of a document. The adapters produce a document representation, which is sent to the Watson application when deemed necessary. ...
Our central claim is that user interactions with everyday productivity applications (e.g., word processors, Web browsers, etc.) provide rich contextual information that can be leveraged to support just-in-time access to task-relevant information. We discuss the requirements for such systems, and develop a general architecture for systems of this type. As evidence for our claim, we present Watson, a system which gathers contextual information in the form of the text of the document the user is manipulating in order to proactively retrieve documents from distributed information repositories. We close by describing the results of several experiments with Watson, which show it consistently provides useful information to its users. Keywords Intelligent information access, resource discovery, context, information agent. 1. INTRODUCTION: THE PROBLEM OF CONTEXT Traditional information retrieval systems [29] have become the cornerstone of information access on the Internet (e.g., [2, 14, 1...
... What if search context could be automatically inferred? This is the goal of the Watson project [11,12,13]. Watson attempts to model the context of user information needs based on the content of documents being edited in Microsoft Word, or viewed in Internet Explorer. ...
Web search engines generally treat search requests in isolation. The results for a given query are identical, independent of the user, or the context in which the user made the request. Nextgeneration search engines will make increasing use of context information, either by using explicit or implicit context information from users, or by implementing additional functionality within restricted contexts. Greater use of context in web search may help increase competition and diversity on the web.
