APPLYING SEMANTIC TECHNOLOGY TO A DIGITAL LIBRARY in Visual Studio .NET

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with simply the required information, drawn from all the relevant documents. Experimentation is necessary to understand what the user wants. Underlying whatever techniques are used must be the insight of Herbert Simon, re-quoted in (NSF, 2003): information . . . consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention, and a need to allocate that attention ef ciently among the overabundance of information sources that might consume it . Our rst priority is always to ensure that the right information is presented to the user. The next priority must be to ensure that it is done in a way which minimises the consumption of that user s attention. 11.3.2.6. Connecting Ideas, Connecting People In an earlier section, we noted that the Perseus Digital Library project had a commitment to connect more people through the connection of ideas . This statement embodies the idea that a digital library should be a community of people as well as a collection of documents. By understanding usage patterns at the semantic level, semantic technology can identify experts as well as communities of interest. In the former case these experts will hopefully be available to give advice, although possibly through the intermediary of the digital library to provide them with anonymity. In the latter case, we hope to help create communities of mutually supportive users with common interests.
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The development of any system should be guided by a comprehensive view of what users actually want from that system. At the same time, asking users about their requirements is notoriously dif cult. When the proposed system includes radically new functionality with which the user is not familiar, users may expect too much from the technology. Frequently, however, they expect too little and ask for more of the same, but simply faster and cheaper. Even when the potential of a new technology is described, there is a difference between imagining the possibilities and actually using the resultant system. Hence any system design using previously untried technology must take into account what users say they want, but at the same time not let user feedback close off any avenues which use the technology in radically new ways. Within the digital library case study in the SEKT project a number of methods were employed to obtain a comprehensive view of what users want from digital libraries, so that these requirements could be interpreted in terms of the capabilities of semantic technology. Initially a questionnaire and focus group were used to gauge user requirements. Much that was learned was very generic and did not relate
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particularly to the capabilities of semantic technology. However, we did learn that our users wanted improved ways of searching, including the ability to search on attributes of a document; and that they wanted searches to take into account their pro le of interests. The next stage was a questionnaire which asked speci c questions about search functionality. Just under 90 people responded to this questionnaire. The responses revealed considerable enthusiasm for a facility which summarised a set of results. A search function which took into account personal preferences was also popular, as was attributebased search. Also well up the list of requirements was the ability, if a particular article was not available in the digital library, to search it out on the Web. Amongst the other popular features were:  A search function which suggests candidate topic areas in which to search.  The ability to enter natural language queries.  The highlighting of named entities, for example people and companies, and access to further information about those entities. Less popular was an application to perform regular searches motivated by personal information, for example held in the user s calendar. The majority of people ranked this useful , but only a very small number ranked it very useful , suggesting that enthusiasm for such proactive systems is lukewarm. Our nal technique for understanding users requirements was that of user preference analysis. The essence of this is to investigate the trade-off, from the user s perspective, between various proposed enhancements. One comparison was between precision and recall. Semantic technology can in principle improve both. Precision is enhanced by the ability to specify the nature of the entity being sought, for example that the string BT corresponds to a company in the telecommunications sector. Recall is enhanced by the ability to understand that different text strings represent the same entity, for example the George Bush , George W Bush and The President all describe the same person. Nevertheless, there is some trade-off between the two capabilities. Systems which are too keen to identify equivalences, in the interests of recall, may do so at the risk of creating false equivalences and damaging precision. A sample of users was asked to rate their preference between these two capabilities. When the results were analysed, there appeared to be two clusters of users: one with a clear preference for precision and another where the users gave equal weight to precision and recall. These studies should only be taken as a guide. When users are confronted with real systems they are likely to react differently than when confronted with questionnaires and in focus groups. However, they offer a starting point for understanding users, to be taken into
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