Agents and the Semantic Web

There are a number of vocabulary terms we use, and sometimes abuse, in the AI community. These terms become even more confusing when we interact with other communities, such as web toolkit developers, who abuse some of the very same terms. One example of such a term is ontology, which was traditionally defined as ′the science or study of being′ (Oxford English Dictionary). In AI, usually attributed to (Gruber, 1993) the notion of ontology is, essentially, "the specification of a conceptualization" -- that is, defined terms and relationships between them, usually in some formal (preferably machine-readable) manner. Even more complicated is the relationship between ontologies and logics — some people treat ontology as a subset of logic, some treat logic as a subset of ontological reasoning, and other uses have been bandied about.

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In this paper, I will use these word s as it is currently being used in "semantic web" circles --that, is, as a set of knowledge terms, including the vocabulary, the semantic interconnections and some simple rules of inference and logic, for some particular topic. For example the ontology of cooking and cookbooks includes ingredients, how to stir and combine them, the difference between simmering and deep-frying, the expectation that the products will be eaten or drunk, that oil is for cooking in or consuming and not for lubrication, and so forth. More complex logics and inference systems are generally considered as separate from the ontology per se. Figure 1, from a talk given by Tim Berners-Lee at the recent XML-2000 Conference (Washington DC, Dec, 2000), shows the proposed layers of the semantic web, with higher level languages using the syntax (and semantics) of lower levels. This paper focuses primarily on the ontology language level, and the sort of agent-based computing that they enable. Higher levels (with complex logics and the exchange of proofs to establish trust relationships) will enable even more interesting functionality, but are left for discussion in later papers. 数据挖掘研究院

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Recently, a number of research groups have been developing languages in which to express ontological expressions on the web (see 数据挖掘研究院

In this paper, I will not describe the DAML language effort or other languages aimed at enabling semantics on the web. Rather, I want to look at some potential applications of these web semantics and consider some challenges we as a research community should be attacking. In particular, I want to look at how information agents and ontologies can together provide breakthrough technologies for web applications.

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The Semantic Web, as I envision it evolving, will not be primarily comprised of nice neat ontologies that have been carefully constructed by expert artificial intelligence researchers. Rather, I envision a complex web of semantics ruled by the same sort of anarchy that currently rules the rest of the web. Rather than a few large, complex, consistent ontologies, shared by great numbers of users, I envision a great number of small ontological components largely created of pointers to each other and developed by web users in much the same way that web content is currently created. 数据挖掘论坛

I predict that in the next few years virtually every company, university, government agency or ad hoc interest group will want their web resources linked to ontological content –because of the many powerful tools that will be available for using it. Information will be exchanged between applications, allowing computer programs to collect and process web content, and to exchange information freely with each other. On top of this infrastructure, agent-based computing will become much more practical, in fact distributed computer programs interacting with non-local web-based resources may eventually become the dominant way in which computers interact with humans and each other, and will be a primary means of computation in the not-so-distant future.

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However, for this vision to become a reality, a phenomenon similar to the early days of the web must occur. Web users will not markup their web pages unless they perceive a value to doing so, and tools to demonstrate this value will not be developed unless web resources are marked up. To help in solving this chicken and egg problem, DARPA is now funding a set of researchers both to develop freely available tools, and to provide significant content for these tools to manipulate – thus demonstrating to the government and other parts of society that the semantic web can be a reality, not just a vision. However, we still need more – without some killer applications showing the great power of web semantics, it will still be a long row to hoe. While I don’t claim to have all the answers, perhaps some of the ideas in the remainder of this paper will inspire the creation of some exciting web-agent applications. 数据挖掘研究院

I will develop this vision a step at a time – describing the creation of pages with ontological information, the definition of services in a machine-readable form, and the use of logics and agents that traverse such a web providing a number of new capabilities.

A crucial aspect of creating the semantic web is to make it possible for a number of different users to create the machine-readable web content without being logic experts. In fact, ideally most of the users shouldn’t even need to know that web semantics exists. Lowering the cost of markup isn’t enough – for many users it needs to be free. That is, semantic markup should be a by-product of normal computer use. Much like current web content, a small number of tool creators and web ontology designers will need to know the details, but most users will not even know ontologies exist.

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As an example, consider any of the well-known products for creating on-line slide shows. Several of these products contain libraries of clippings that can be inserted into the presentations. These clippings can be marked with pointers to ontologies by the developers of the software, and the saving of the products on the web (Save as HTML…), could include the linking of these saved products to the ontologies they’re marked from. Thus a presentation that had pictures of, for example, a cow and a donkey, would be linked to barnyard animals, mammals, animals, etc. While this would not guarantee appropriate semantics (the cow might be the mascot of some school or the donkey the icon of some political party), retrieval engines would be able to use the markups as clues to what are in the presentations and how they may be linked to other ones. The user simply creates a slide show as is done today, but the search tools do a better job of finding it based on content.

An alternative example would be a markup tool driven from one or more ontologies. For example, consider a homepage-creation tool that is driven by representing hierarchical class relations as menus. Properties of the classes could be tied to various types of forms, and these made available via simple web forms. A user could thus choose from a menu to add information about a person, and thence choose a relative (vs. friend, professional acquaintance, etc.) and thence a daughter. The system could then use the semantics to retrieve the properties of daughters specified in the ontology/ies and to display them to the user as a form to be filled out by filling in strings (like name), numbers (age); or to browse for related links (homepage), on-line images (photo-of), etc. The system would then lay these out using appropriate web tools, while also recording the relevant instance information.

Since the tool could be driven from any ontology, a library of terms could be created (and mixed) in any number of different ways. Thus, a single easy-to-use tool would allow the creation of home pages (using ontologies on people, hobbies, etc.), professional pages (using ontologies relating to specific occupations or industries), agency-specific pages (using ontologies relative to specific functions), etc. In an easy, interactive way a user would be assisted in creating a page and get the markup created for free. Notice, also, that mixtures of the various ontologies and forms could be easily created, thus helping to create the semantic web of pages linking to many different ontologies, as mentioned earlier.

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Not only can pages be created with links to numerous ontologies, but also the ontologies themselves can include links between them to reuse (or change) terms. The notion of creating large ontologies by the combination of components is not unique to the semantic web vision (c.f. Clark and Porter, 1997). However, the ability to link and browse ontological relations enabled by the web’s use of semantics will be a powerful tool for those users who do know what ontologies are and why they should be used.

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How will this work? Consider Mary, the web master for a new business-to-consumer web site for an online pet shop. Browsing through a web ontology repository (such as the one currently hosted at http://www.daml.org/ontologies/), she finds that there are a lot of interesting ontologies available. Selecting one of these, a product ontology, Mary uses a browser to choose the various classes and relations that she wants to include in her own ontology. Several of these may be need to be further constrained based on properties of her particular business. For example, Mary must define some of these properties for the various animals she will sell, and so on. 数据挖掘工具

Searching further in the ontology repositories, she finds that there is a biological taxonomy that contains many classes such as feline, canine, mammal, animal, etc. and that these contain several properties relevant to her business, so she provides links to these. She adds a new descriptor field to animal called "product-shipping-type" and sets it to default to the value "alive" (not a standard property or default in the product ontology she chose to extend). Finally, she notices that although the biological ontology contained a number of kinds of felines, it didn’t use the categories she wanted (popular pets, exotic pets, etc.) She adds these classes as subclasses of the ones in the parent ontology and defines their properties. Saving this ontology on her web site, she is now able to use other ontology-based tools to help organize and manage her web site. Mary is motivated to add the semantics to her site both by these tools, and the other powerful browsing and search tools enabled by the semantics. 数据挖掘工具

Following this, the many ontology-based search and browsing tools on the web, when pointed at her pages, are able to use this information to help distinguish her site from the many other (non-ontology based) sites being used by her competitors. This makes it easy for her to extend her site to use various B2B e-commerce tools that can take advantage of web ontologies for automated business tools. In addition, she may choose to submit her ontology back into one of the repositories, so that others in her profession can find it and use it for their own sites. After all, the power of the ontologies is in the sharing, and the more people using common terms with her, the better. 数据挖掘交友

One of the most powerful uses of the web ontologies described heretofore, and a key enabler for agents on the web, is in the area of web services. Recently, numerous small businesses, particularly those in the area of supply-chain-management for B2B e-commerce, have been discussing the role of ontologies in managing the machine-to-machine interactions. In most cases, however, these approaches have assumed that the ontologies are primarily used by the constructors of computer programs to make sure that they agree on terms, types, constraints, etc. Thus, the agreement is recorded primarily off line, and used in web management applications. On the semantic web we will go much further than this, creating machine-readable ontologies used by "capable" agents to find these web services and automate their use.

A well-known problem with the web of today is the difficulty in finding the many web services currently available on line. For example, back when I first started writing this article, I wanted to send a web greeting card, but didn′t know the name of one of the companies offering such a service. Using standard keyword based searches did not help me much. The query "Web Greeting Card" found many hits from people who are displaying particular greeting cards, or who have these three terms at various places on their pages . In fact, these three keywords given to several of the most common search engines did not turn up the most popular of the web greeting card service provider in their top 20 suggestions. (A search on "eCards" would indeed find this site, but I didn′t happen to know this particularly ugly neologism.) As I edit this paper for final consistency, the search engines are now finding this page, but if I want something more complex -- for example, an anniversary card for my mother-in-law that plays Hava Nagila, I′m still pretty much out of luck. As the number of services grows, and the specificity of our needs increases, the ability of current search engines to find the most appropriate services is strained to the limit.

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A number of efforts are currently underway to help improve this situation (c.f. UDDI, 2000; ebXML, 2000; eSpeak, 2000). These efforts focus on what one may call a "service advertisement." By creating a controlled vocabulary of service advertisements, search engines could find these web services. Thus, Mary’s Pet Site, as discussed above, might have an annotation that it provides a "Sell" service of object "Pet" and thus pet buyers would more easily be able to find it. Similarly, a web greeting card site could register as something like a "personal service, e-mail, communications" and a user could more easily get to it without knowing the term "ecard." 数据挖掘工具

However, I argue that semantic web techniques can, and must, go much further. The first use of ontologies on the web for this purpose is pretty straightforward – by creating the service advertisements in an ontological language, tools could use the hierarchy (and property restrictions) to find matches via the class/subclass properties or other semantic links. For example, someone looking to buy roses might find florists (who sell flowers) even if there were no exact match that served the purpose. Using, for example, description logic (or other inferential means), the user could even find categorizations that weren’t explicit. So, for example, specifying a search for animals that were of "size = small" and "type = friendly," the user could end up finding the Pet Shop Mary is working for, which happens to specialize in hamsters and gerbils. 数据挖掘交友

Futhermore, using a combination of web pointers, web markup, and ontology languages, we can do even better than just putting service advertisements into ontologies. Rather, using these techniques we can also include a machine-readable description of a service (as to how it runs) and some explicit logic describing the consequences of using the service. In fact, it is these latter two properties – a service description and a service logic – that would lead us to the integration of agents and ontologies in some exciting ways, as I will discuss in the next section.

In an earlier article (Hendler, 1999), I described a vision of intelligent web agents using the analogy of travel agents – rather than doing everything for a user, the agents would find possible ways to meet user needs, and offer the user choices for their achievement. Much as a travel agent might give you a list of several flights you could take, or a choice of flying vs. taking a train, a web agent should offer a slate of possible ways to get you what you need on the web. 数据挖掘工具

Consider the following example (a web-enabled method for saving the doomed crew of The Perfect Storm, Junger, 1997). In this story, now a major motion picture, a crew of fishermen is out at sea when weather conditions conspire to create a storm of epic proportions. For various reasons, the crew is unable to get a detailed weather map, and thus miss the fact that the storm is developing right in their way. Instead of avoiding it, they end up at its center with tragic results. How could web agents have helped? 数据挖掘工具

As the Captain of the ship goes to call land, a wave hits and his cell-phone is swept overboard. Luckily, he is a savvy web user, and has brought his wireless web device with him as well. 数据挖掘研究院