ACM Computing Surveys
31(4), December 1999,
http://www.acm.org/surveys/Formatting.html. Copyright ©
1999 by the Association for Computing Machinery, Inc. See the permissions statement below.
Automatic Link Generation
Mathematical and Information Sciences
723 Swanston St., Carlton 3053
Email: Ross.Wilkinson@cmis.csiro.au Dublin City University
School of Computer Applications
Dublin 9, Ireland
Hypertextual navigation from known locations has some advantages over search. Two of these key advantages are that content creators can provide carefully-defined specific relationships, and that users of the information have a context in which to understand information. However these advantages can be difficult to realise as the size of the information space grows. Some of the problems are:
Besides the issue of the types of links being created, we should also examine whether the links are static or dynamic. While most links created in the World Wide Web are static, there are good reasons for having links that are determined at the time that a piece of information is being displayed. As has already been mentioned, only in a dynamic hypertext environment can the user's contextual situation, which must be an important consideration in hypertext navigation, be considered. Dynamic link production can also guarantee that no dangling links are displayed, and can allow links to be created from and to material that the link author does not control [Ashman 1997] . The value of creating dynamic links that take context into account demonstrates the importance of open hypertext systems such as Microcosm [Davis 1993] and Hyper-G [Andrews 1995a] .
If source information is already well-described structurally, it is comparatively easy to turn text into hypertext. Early work of Frisse [Frisse 1988] converted a medical handbook using the book's hierachical structure, and with increasing use of SGML and XML to code information it is easy to construct nodes and associated links to represent this information in navigable form [Fahmy 1990] [Fuller 1993].
To create static links between semantically related text, we can simply calculate the similarity between all pairs of information, and then insert links between those that are most similar. This assumes that similarity, as measured by information retrieval techniques, mirrors semantic relatedness, and has been used to good effect. There are many ways of measuring similarity and then determining whether a link should be in place. Many authors have described work on approaches like this and it was particularly important at a time when processing speeds meant that pre-computation was attractive. Furuta et al. describe a comparative study of the quality of links produced [Furuta 1989] . Salton et al. describe building a set of cross-references for an encyclopedia [Salton 1991] and Lelu created links using both similarity and spreading activation [Lelu 1991]. Green introduced the use of lexical chains, exploiting the semantic relatedness of individual words, to determine when links should be used [Green 1998]. Allen demonstrated that there is value in distinguishing between the various sub-types of semantic links, and demonstrated how links associated with these sub-types can be determined and assigned [Allan 1997]. Because links created in this way will vary in quality considerably, it is possible to generate them automatically, but manually vet them [Bernstein 1990] [Chignell 1991].
By integrating a query engine into a hypertext system, it is also possible to create dynamic semantic links. This can be as simple as calculating the similarity between the currently viewed information and all other pieces, and presenting those that are most similar, to explicitly inserting a query as a link [Boy 1991] [Coombs 1990] [Rivlin 1994]. This became attractive as search engines got faster, but fully automatic link generation does have problems. If a similarity threshold is used, there tends to be a very uneven creation of links with huge numbers of links to and from some objects and no paths to others. This effect of this problem can be measured with metrics such as those developed by Botafogo et al. [Botafogo 1992] [Rivlin 1994] which measure the overall structural characteristics of a graph or hypertext in terms of its connectedness or its linearity. In practice, however, such metrics have not been found to be very useful in large or even medium-sized hypertexts as they tend to be suitable for measuring graph topology in a local rather than global setting. In an interesting report on integrating search and hypertext, Tebbutt [Tebbutt 1999] showed that there is value in this integration, but that user's reaction varies widely, and that there are many issues to do with what information is shown, and how, that must be resolved in a successful synthesis. One of the issues that the users raised was the number of links that ought be generated. This raises the larger issue of what is the appropriate structure(s) of a hypertext? Should there be tightly clustered sets of pages created? How should a structure associated with automatically generated links be related to, say, an explicit structure already in place? What models of the information space best support a variety of information discovery activities?
Instead of creating links depending solely on current location, it is
also useful to take into account the overall information need of the information
seeker. One way of doing this is to dynamically build guided tours, based
on an initial description of information need
Calvi and de Bra
describe methods of determining relevant links based on the learning state
of the user of a training hypertext. In this case the model of the user
is more complicated than is the case in both hypertext (where the location
of the user in the information space is known) and in information retrieval
(where an explicit query is known). To exploit more fully the power of
automatically created links at the time of use, we need more sophisticated
user models which take into account not only location, explicit needs,
but user history, and long standing user preferences. We may well wish
to build discourse models that recognise that exploring an information
space is an activity that unfolds.
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[Tebbutt 1999] John Tebbutt. "User evaluation of automatically generated semantic hypertext links in a heavily used procedural manual" in Information Processing and Management, 35(1), 1-18, 1999.
[Thistlewaite 1997] Paul Thistlewaite. "Automatic construction and management of large open webs" in Information Processing and Management, 33(2), 161-173, 1997.
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