Useful Search Links and References

Essays in this search series:

Articles and Studies

Search and You May Find
Jakob Nielsen’s Alertbox for July 15, 1997, discussing search, navigation, and the way users employ both.
What’s Wrong with Internet Searching
Abstract: This paper argues that the model of searching for information on the Web as used by many existing search engines does not meet the needs of Internet-naive (but PC-literate) users. This is based on two user trials carried out in the summer of 1995 with people who had not encountered the Internet before. Results show that potential users need at least some understanding of basic Internet concepts in order to carry out successful searches. Without this understanding, potential customers are likely to be discouraged from taking up Internet services after initial bad experiences.
[broken link Why On-Site Searching Stinks]
Jared Spool: In our most recent web-site studies, we watched users look for information within web sites. Our goal was to gather data about what makes a good link, but we did not tell users whether or not they should use the site’s search facilities. Users went to these search engines in almost half the tasks. Maybe they shouldn’t have.
Clarifying Search: A User-Interface Framework for Text Searches
Abstract: Current user interfaces for textual database searching leave much to be desired: individually, they are often confusing, and as
a group, they are seriously inconsistent. We propose a four- phase framework for user-interface design: the framework provides common structure and terminology for searching while preserving the distinct features of individual collections and search mechanisms. Users will benefit from faster learning, increased comprehension, and better control, leading to more effective searches and higher satisfaction.
Digital Libraries: Searching Is Not Enough
Excerpt: …This image of what users should be able to do with Digital Libraries is far too narrow. That became evident from a series of interviews conducted with workers in a large, diverse company producing computers, computer peripherals, medical-, and microwave equipment. The goal was to learn about information needs and habits of workers in technical work settings. Occupations of our informants included technical support, marketing, software integration, finance, electronics product design, chemical analysis instrument design and design/manufacture of computer printers. The interviews were semi-structured and were conducted within the interviewee’s work space. We had an opportunity to view information artifacts, and in some of the cases, we witnessed the work being conducted.
Evaluating Quality on the Net
Excerpt from introduction: With the growth of information on the Internet and the development of more sophisticated searching tools, there is now the more likely possibility of finding information and answers to real questions. But, within the morass of networked data are both valuable nuggets and an incredible amount of junk.
Mapping Entry Vocabulary to Unfamiliar Metadata Vocabularies
Excerpt: The emerging network environment brings access to an increasing population of heterogeneous repositories. Inevitably, these, have quite diverse metadata vocabularies (categorization codes, classification numbers, index and thesaurus terms). So, necessarily, the number of metadata vocabularies that are accessible but unfamiliar for any individual searcher is increasing steeply. When an unfamiliar metadata vocabulary is encountered, how is a searcher to know which codes or terms will lead to what is wanted? This paper reports work at the University of California, Berkeley, on the design and development of English language indexes to metadata vocabularies.
Modeling Users’ Successive Searches in Digital Environments
Excerpt from Abstract: As digital libraries become a major source of information for many people, we need to know more about how people seek and retrieve information in digital environments. Quite commonly, users with a problem-at-hand and associated question-in-mind repeatedly search a literature for answers, and seek information in stages over extended periods from a variety of digital information resources. The process of repeatedly searching over time in relation to a specific, but possibly an evolving information problem (including changes or shifts in a variety of variables), is called the successive search phenomenon. The study outlined in this paper is currently investigating this new and little explored line of inquiry for information retrieval, Web searching, and digital libraries.
What Do People Want from Information Retrieval?
Excerpt: In this paper, I summarize the experience of the National Science Foundation (NSF) Center for Intelligent Information Retrieval (CIIR)
in the area of industrial and government research priorities.
Cognitive Strategies in Web Searching
Excerpt from Abstract: Usability tests have shown that users often get lost very easily on the Internet when looking for information. However, we still know very little about why this is so and how it can be avoided. The goal of our research is to develop an empirically-based model of web searching, to help explain how people search for information on the Web and to develop guidelines for supporting Web searching. Also see the accompanying PowerPoint presentation shown at HFweb99.

Books that Discuss Search Issues

[newer version Information Architecture for the World Wide Web]
By Louis Rosenfeld and Peter Morville.
Web Site Usability: A Designer’s Guide
By Jared Spool, et al.
[outdated Practical Digital Libraries: Books, Bytes and Bucks]
By Michael Lesk.

Search Engine Information

[broken link Search Engine Glossary]
A list of some common search-related terms and their definitions.
[broken link Glossary for Information Retrieval]
Excerpt: This page attempts to give definitions for all of the terms relevant to Information Retrieval. This doesn’t include names of specific projects, engines, or people.
How Search Engines Work
Excerpt: The term “search engine” is often used generically to describe both true search engines and directories. They are not the same. The difference is how listings are compiled.