Search results

This paper explores the possibility of adding user‐oriented class associations to hierarchical library classification schemes. Some highly associated classes not grouped in the same subject hierarchies, yet relevant to users’ knowledge, are automatically obtained by analyzing a two‐year log of book circulation records from a university library in Taiwan. The library uses the Chinese Decimal Classification scheme, which has similar structure and notation to the Dewey Decimal Classification. Methods, from both collaborative filtering and information retrieval research, were employed and their performance compared based on similarity estimation of classes. The results show that classification schemes can, therefore, be made more adaptable to changes of users and the uses of different library collections by analyzing the circulation patterns of similar users. Limitations of the methods and implications for applications are also discussed.

This study aims to examine the differences between web image and textual queries.

A large number of web queries from image and textual search engines were analysed and compared based on their factual characteristics, query types, and search interests.

Useful results include the findings that web users tend to input short queries when searching for visual or textual information; that image requests have more zero hits and higher specificity, and contain more refined queries; that web image requests are more focused than textual requests on some popular search interests, and that the variety of textual queries is greater than that of image requests.

This study provides results that may enhance one's understanding of web‐searching behaviour and the inherent implications for the improvement of current web image retrieval systems.

Clustering web search results into dynamic clusters and hierarchies provides a promising way to alleviate the overabundance of information typically found in ranked list search engines. This study seeks to investigate the usefulness of clustering textual results in web search by analysing the search performance and users' satisfaction levels with and without the aid of clusters and hierarchies.

This study utilises two evaluation metrics. One is a usability test of clustering interfaces measured by users' search performances; the other is a comprehension test measured by users' satisfaction levels. Various methods were used to support the two tests, including experiments, observations, questionnaires, interviews, and search log analysis.

The results showed that there was no significant difference between the ranked list and clustering interfaces, although participants searched slightly faster, retrieved a larger number of relevant pages, and were more satisfied when using the ranked list interface without clustering. Even so, the clustering interface offers opportunities for diversified searching. Moreover, the repetitive ratio of relevant results found by each participant was low. Other advantages of the clustering interface are that it highlights important concepts and offers richer contexts for exploring, learning and discovering related concepts; however, it may induce a certain amount of anxiety about missing or losing important information.

The evaluation of a clustering interface is rather difficult, particularly in the context of the web search environment, which is used by a large heterogeneous user population for a wide variety of tasks. The study employed multiple data collection methods and in particular designed a combination of usability and comprehension tests to offer preliminary results on users' evaluation of real‐world clustering search interfaces. The results may extend the understanding of search characteristics with a cluster‐based web search engine, and could be used as a vehicle for further discussion of user evaluation research into this area.