Information retrieval (IR) is an important part of many tasks performed by people when they use computers. However, most IR research and theory isolates the IR component from the tasks performed by users. This is done by expressing user needs as a query performed on a database. In contrast this dissertation investigates the design and evaluation of information retrieval systems where the information retrieval mechanisms remain embedded in the user tasks. While there are a many different types of user tasks performed with computers we can specify common requirements for the IR needed in most tasks. There are both user interface and machine processing requirements. For user interfaces it is desirable if users interact directly with information databases, keep control of the interaction and are able to perform IR in a timely manner. Machine processing has to be within the capabilities of machines yet must fit with human perceptions and has to be efficient in both storage and computation. Given the overall requirements, the dissertation gives a particular implementation for how to embed IR in tasks. The implementation uses a vector representation for objects and organises the objects in a near neighbour data structure. Near neighbours are defined within the context of the tasks the users wish to achieve. While the implementation could use many different finding mechanisms, it emphasises a constructive solution building approach with localised browsing in the database. It is shown how the IR implementation fits with the overall task activities of the user. Much of the dissertation examines how to evaluate embedded IR. Embedded IR requires testing users' task performance in both real experiments and thought experiments. Implementation is tested by finding known objects, by validating the machine representations and their correspondence with human perceptions and by testing the machine performance of the implementation. Finally implications and extensions of the work arc explored by looking at the practicality of the approach, other methods of investigation and the possibility of building dynamic learning systems that improve with use.

Cílem mé diplomové práce bylo navrhnout metodu analýzy retinálních sekvencí, která bude hodnotit kvalitu jednotlivých snímků. V teoretické části se také zabývám vlastnostmi retinálních sekvencí a způsobem registrace snímků z fundus kamery. V praktické části je implementována metoda hodnocení kvality snímků, která je otestována na reálných retinálních sekvencích a vyhodnocena její úspěšnost. Práce hodnotí i vliv této metody na registraci retinálních snímků.