Conclusions and Future Directions

The emergence of the Internet has allowed millions of people to use a variety of electronic information retrieval (IR) systems, such as digital libraries, Web search engines, online databases, and Online Public Access Catalogues (OPACs). The nature of IR is interaction. Interactive information retrieval is defined as the communication process between the users and the IR systems. However, the dynamics of interactive IR is not yet fully understood. Moreover, most of the existing IR systems do not support the full range of users’ interactions with IR systems. Instead, they only support one type of information-seeking strategy: how to specify queries by using terms to select relevant information. However, new digital environments require users to apply multiple information-seeking strategies and shift from one information- seeking strategy to another in the information retrieval process.

Implications of the Planned-Situational Interactive IR Model

The planned-situational model of interactive IR not only clarifies some of the important issues of information retrieval but also sets up a foundation for researchers to further explore the nature of interactive IR.

Interactive IR Framework

Representation and comparison are usually considered the two core processes in traditional IR. Comparison is between two representations: representation of text and representation of user need. Much of the research in IR had concentrated on indexing techniques for representing the contents of documents and retrieval techniques that compare documents to queries (Salton & McGill, 1983; van Rijsbergen, 1979). Two underlying assumptions of the traditional IR view are: (1) the information need is static and can be specified; (2) there is only one form of information-seeking behavior (Belkin, 1993).

Interactive IR Models

The nature of information retrieval (IR) is interaction. However, the traditional IR model only focuses on the comparison between user input and system output. It does not illustrate the changeable interaction process (Saracevic, 1997). The human involvement of IR makes the process complicated and dynamic. Belkin (1993) further identified the two underlying assumptions of the traditional IR view: (1) The information need is static, and can be specified; and (2) there is only one form of information-seeking behavior. The limitations of the traditional IR model are becoming more evident. In the 1990s researchers started to develop interactive IR models. Among them, Ingwersen’s cognitive model (1992, 1996), Belkin’s episode model of interaction with texts (1996), and Saracevic’s stratified model (1996a, 1997) are the most cited ones.

Interactive IR in Digital Library Environments

For centuries, people have been used to printed materials. The emergence of the Internet brings dramatic changes to millions of people in terms of how they collect, organize, disseminate, access, and use information. Researchers (Chowdhury & Chowdhury, 2003; Lesk, 2005; Witten & Bainbridge, 2003) have identified the following factors that contributed to the birth of digital libraries: 1. Vannevar Bush’s pioneering concept and idea of Memex. Vannevar Bush (1945) wrote a classic article, “As We May Think,” which has had a major impact on the emergence of digital libraries. In the article, he described his Memex device, which was able to organize books, journals, and notes in different places by linked association. This associative linking was similar to what is known today as hypertext. 2. The advancement in computer and communication/network technology. The computer was first used to manage information. In the 1960s, the emergence of remote online information search services changed the way people access and search information. By the 1980s, people could remotely and locally access library catalogues via Online Public Access Catalogues (OPACs). The invention of the CD-ROM made it easy and cheap for users to access electronic information. Most importantly, Web technology started in 1990, and the occurrence of Web browsers afterwards have enabled users to access digital information anywhere as long as there is an Internet connection. Web search engines offer an opportunity for millions of people to search full-text documents on the Web. 3. The development of libraries and library access. Since the creation of Alexandrian library around 300 B.C., the size and number of libraries have grown phenomenally. A library catalogue goes from a card catalogue to three generations of online public access catalogues started in the 1980s. Library materials include mainly printed resources to multimedia collections, such as images, videos, sound files, and so forth. Simultaneously, the information explosion in the digital age makes it impossible for libraries to collect all of the available materials.

Interactive IR in OPAC Environments

Online catalogs are types of interactive computer systems; they can also be called “interactive catalogs” because a user interacts with the computer to find relevant information. The interaction is the main difference between Online Public Access Catalogs (OPACs) and other types of library catalogs (Hildreth, 1982; Matthews, 1985). Online catalogs are regarded as real-time interactive retrieval systems for libraries (Fayen, 1983). According to Peters (1991), the development of online catalogs can be characterized by three decades of development. In the 1960s, the development of online catalogs was led by the development of computer technology and the library community’s desire to increase efficiency in finding library materials. In the 1970s, commercial vendors started to replace large university libraries as the principal developers of computer-based library systems. In the 1980s, local libraries expand their control of the library catalog systems.

Interactive IR in Online Database Environments

The Internet has introduced the concept and capability of information retrieval to millions of users. There is an increasing growth in databases, producers, vendors, records, and searches. Williams (2006) has monitored the growth of the online industry for about 30 years. From 1975 to 2005, databases increased considerably, from 301 to 17539, database records from 52 million to 21.02 billion, and database entries from 301 to 16532. The number of producers has not grown as fast as databases because one producer might publish multiple databases. The number of publishers increased from 200 to 3208 from 1975 to 2005. In 2005, the average producer produced 5.13 databases. Because each vendor might provide services from multiple databases, the number of vendors grew at a slower pace from 105 to 2811.

Illustration and Validation of the Interactive IR Framework

In order to illustrate and validate the planned-situational interactive IR model, I conducted an empirical study. This study was a pilot of a large-scale study, discussed in the summary of this chapter, that focuses on the investigation of how people seek and retrieve information in their research proposal writing process. The objective of the study is particularly concerned with whether multiple information-seeking strategies were applied and shifts in information-seeking strategies occurred in users’ information-seeking and -retrieving process. This study addressed the following research questions: 1. What are users’ levels of goals/tasks and their representation? 2. What are users’ personal information infrastructures? 3. What is the social-organizational context for users’ information seeking and retrieving? 4. What types of IR systems do users access and what types of influences do these systems have? 5. What are the types of information-seeking strategies employed by users? 6. Do users shift their current search goals and information-seeking strategies in the information-seeking and -retrieving process? If yes, how? 7. What are the factors that lead to different levels and types of shifts? This research helps us understand the nature of information seeking and retrieving, in particular, the nature of interactive IR. Applying emprical data to examine the major components of the planned-situational interactive IR model and their interactions effectively assists us to validate and illustrate this model. The major contribution of this study is that it investigates users’ dynamic information-seeking processes related to their work and search tasks instead of a snapshot of an information- seeking activity. The emprical data further enrich and enhance the interactive IR framework. In addition to this study, I also incorporate some related studies to validate and ilustrate the planned-situational interactive IR model.

Interactive IR in Web Search Engine Environments

Tim Berners-Lee wrote the initial proposal for the World Wide Web in 1989, and developed it online in 1991 by using a hypertext model (Berners-Lee, 1989, 1996). The World Wide Web was developed to allow people to collaborate on projects; it began at CERN, the European Particle Physics Laboratory in Geneva, Switzerland, and expanded across nations and disciplines. Berners-Lee (1996) defined the components of the Web: the boundless information world, the address system (URI), a network protocol (HTTP), a markup language (HTML), a body of data, and the client-server architecture of the Web. The creation in 1993 of Mosaic, a graphic Web interface that was the precursor of Netscape, enabled millions of people to easily access the Web. Since then, the increase in Web resources has been phenomenal, and Web search engines are the essential tools for navigating those Web resources.

TREC and Interactive Track Environments

The Text REtrieval Conference (TREC) is sponsored by three agencies—the U.S. National Institute of Standards and Technology (NIST), the U.S. Department of Defense, Advanced Research Projects Agency (DARPA), and the U.S. intelligence community’s Advanced Research and Development Activity (ARDA)—to promote text retrieval research based on large test collections. Overviews of TREC (Harman & Voorhees, 2006; Voorhees & Harman, 2005) and the TREC Web site (trec.nist. gov) have provided a comprehensive review of TREC conferences. This section is compiled based on these resources. TREC started in 1992 with 25 participating groups, including the leading text retrieval groups, to search two gigabytes of text. For each TREC, NIST offers a test collection and questions. Participating teams follow the guidelines, run the data on their own IR systems, and return the results to NIST. NIST evaluates the submitted results and organizes workshops for participants to discuss their experience and present results. By the end of 2005, 14 TREC conferences had been held.