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6.1. TOOL MARKET

The expert system tool market should show sustained growth in the future. Total sales have grown approximately 17% per year since 1988. This trend should continue. Vendors should continue their strategy to market tools that offer the ability of developing different types of expert systems, such as rule-based, frame-based, and fuzzy logic systems. Developers will then have in one package a set of AI tools to attack a given problem. New types of tools will also enter the market. Vendors in the past have been quick to react to promising new AI techniques. We have seen this recently, for example, with the introduction of CBR and data-mining tools. This is good business strategy. As new AI developments emerge from the laboratory demonstrating potential commercial value, we should see vendors marketing new tools wrapped around the new developments.

6.2. INTEGRATION

The early expert systems were stand-alone systems that were not linked to other conventional software programs or other computer systems. Some of the most valuable applications today are ones where an expert system works hand-in-hand with established software, such as a database management system (DBMS). Most tools today permit the development of an expert system that is relatively easy to integrate with conventional software environments. This trend will no doubt continue as the technology is no longer viewed as a research curiosity, but rather a powerful tool for solving practical real-world problems. The increased interest in the use of an expert system in a support role, such as intelligent agent in a large established software application, will also add to this trend.

6.3. DOMAIN-SPECIFIC TOOLS

Expert system tool vendors have been very responsive to the needs of the buyers of their tools. Early on, the typical buyer was looking to "test the water," exploring the potential of the technology. To accommodate this buyer, vendors offered general-purpose tools that could be used for a wide range of applications. Today, buyers are looking for tools that aid in the development of an expert system for a specific activity, such as process control, manufacturing scheduling, and so on. Responding to this need, vendors have begun to market domain-specific tools. Sales of these tools presently dominate the market and should show substantial growth in the future.

6.4. AUTOMATED KNOWLEDGE ACQUISITION

The majority of time spent when developing an expert system is with the knowledge acquisition task. Decreasing this time would significantly decrease development costs. One way to accomplish this is through software tools that would support knowledge acquisition activities. One promising area is self-learning systems. We have already discussed induction systems and their ability to uncover decision-making knowledge from a large set of examples. Another type of self-learning system would attempt to discover knowledge from database information (subject of Section XX). Because of the high costs of knowledge acquisition and the potential value offered by automated knowledge acquisition tools, we should see more of these types of tools available in the future.

6.5. KNOWLEDGE DISCOVERY IN DATABASES

One of the more exciting and potentially valuable AI applications on the horizon is knowledge discovery in databases (KDD). Given a database containing a large amount of data, KDD attempts to discover useful knowledge from the data. In the business arena, for example, the discovered knowledge could be potentially useful in such applications as assisting in financial investment advising, aiding fraud detection in financial transactions, and predicting marketing trends for a given product line. KDD is a multistep process, with data mining being one of the steps that extracts patterns from the data that are later used for knowledge discovery. Data mining tools have been a recent introduction into the market, and it shouldn't be long before vendors begin to offer KDD tools. For an excellent review of KDD, see Fayyad et al. (1996).

6.6. WORLD WIDE WEB

One very specialized area where we should see expert system applications in the future is in the areas of the internet and the World Wide Web (WWW). The WWW is growing exponentially, and so is the quantity of information that resides there. Even with the presently available search engines, intelligently navigating the WWW is a non-trivial task. Within seconds, these engines provide a list of sites where you can obtain information on the search subject. That's the good news. The bad news is that all too often there is either too much information to digest or irrelevant information. Infoseek's CEO Robin Johnson comments, "The best search engine is the one between your ears," -- a target familiar to expert system developers.

The meteoric rise in the interest in the internet, coupled with the need for intelligent information retrieval, will serve as a magnet to expert system developers. Several expert system vendors, recognizing the potential of this emerging market, have already begun to offer internet-related products. Some of these have products that enable the WWW to serve as a front-end to server-based expert systems. They include Exsys, Neuron Data, Talarian, Inference, and Gensym. Level5 Research offers Level5 Quest, a fuzzy search and retrieval tool, which can be used for searching internet database applications by WWW browsers. We should see considerable AI activity in this area in the future, and tool vendors should be there quickly to support the effort.


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