Amazon CloudSearch is a new hosted search service, built on top of many cloud-based AWS services, and based on the same technology that powers search on Amazon's retail sites. Because of its ease of configuration and scalability, CloudSearch represents the next step in the democratization of information retrieval. This democratization process, increasing access to search for both end users and potential search providers, has continued over several decades, through technologies like early online metered search services, enterprise search software, web search, and open source search tools. CloudSearch further reduces barriers to entry, allowing a person or organization to basically say "make my content searchable" and have it happen automatically. CloudSearch may also offer an opportunity to overcome the stagnation that has occurred in search user experiences over the past 15 years. When you no longer need to be a search expert to make your content available, you're not stuck with ten blue links. Instead, you can focus on providing the kind of interaction that makes sense for your application and your users. CloudSearch enables a flowering of search applications that need not be tied to the web, and an opportunity to explore new ways of interacting with information retrieval technology.

Powerful SIMD instructions in modern processors offer an opportunity for greater search performance. In this paper, we apply these instructions to decoding search engine posting lists. We start by exploring variable-length integer encoding formats used to represent postings. We define two properties, byte-oriented and byte-preserving, that characterize many formats of interest. Based on their common structure, we define a taxonomy that classifies encodings along three dimensions, representing the way in which data bits are stored and additional bits are used to describe the data. Using this taxonomy, we discover new encoding formats, some of which are particularly amenable to SIMD-based decoding. We present generic SIMD algorithms for decoding these formats. We also extend these algorithms to the most common traditional encoding format. Our experiments demonstrate that SIMD-based decoding algorithms are up to 3 times faster than non-SIMD algorithms.

We conducted a series of experiments in which surveyed web search users answered questions about the quality of search results on the basis of the result summaries. Summaries shown to different groups of users were editorially constructed so that they differed in only one attribute, such as length. Some attributes had no effect on users' quality judgments, while in other cases, changing an attribute had a "halo effect" which caused seemingly unrelated dimensions of result quality to be rated higher by users.

Abstract User interfaces of Web search engines reflect attributes of the underlying tools used to create them, rather than what we know about how people look for information. In this article, the author examines several characteristics of user search behavior: the variety of information‐seeking goals, the cultural and situational context of search, and the iterative nature of the search task. An analysis of these characteristics suggests ways that interfaces can be redesigned to make searching more effective for users.

Previous work on understanding user web search behavior has focused on how people search and what they are searching for, but not why they are searching. In this paper, we describe a framework for understanding the underlying goals of user searches, and our experience in using the framework to manually classify queries from a web search engine. Our analysis suggests that so-called navigational" searches are less prevalent than generally believed while a previously unexplored "resource-seeking" goal may account for a large fraction of web searches. We also illustrate how this knowledge of user search goals might be used to improve future web search engines.

This paper proposes a new type of asynchronous group communication tool called an information rendezvous system. The purpose of the system is to mediate between producers and consumers of information. Among other attributes, information rendezvous systems rely on the knowledge of the user community in determining the relevance of information. We also two describe two prototypes that demonstrate the feasibility of the information rendezvous concept.

We describe a prototype system called Me~ageWorld designed to offer a new approach to online communication.MessageWorld provides an alternative to traditional group information sharing tools such as e-mail, online bulletin boards, and searchable storage archives.MessageWorld relieves message authors of the burden of addressing, while prospective readers are relieved of the burden of searching; the system provides a rendezvous mechanism for uniting readers with messages of interest to them.We rely on a variety of techniques including traditional content analysis and the correlation of user preferences.Adaptive algorithms serve to incorporate some of the knowledge of the user community in the system's assessment of each user's interests.1

The pile is a new element of the desktop user interface metaphor, designed to support the casual organization of documents. An interface design based on the pile concept suggested uses of content awareness for describing, organizing, and filing textual documents. We describe a prototype implementation of these capabilities, and give a detailed example of how they might appear to the user. We believe the system demonstrates how content awareness can be not only used in a computer filing system, but made an integral part of the user's experience.

SCALIR is a legal information retrieval system which uses a combination of symbolic and connectionist artificial intelligence techniques. Traditional systems used for automating legal research have many difficulties which make them “brittle”; SCALIR is an attempt to rectify many of these problems. SCALIR's hybrid nature is especially appropriate for the legal domain, which requires both logical and associative inferences. The system also benefits from a unique direct-manipulation style interface and the ability to improve its performance based on user feedback.