Learning Interaction Models in a Digital Library Service

Semeraro, Giovanni; Ferilli, Stefano; Fanizzi, Nicola; Abbattista, Fabio

doi:10.1007/3-540-44566-8_5

Cited by 15 publications

(7 citation statements)

References 10 publications

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“…This kind of collection personalization can be assisted by server‐side tools that profile the content of the library, maintain personal filters, and customize retrieval mechanisms (Jayawardana, Hewagamage, & Hirakawa, 2001). Ways for users to change their perspectives, and hence their interface and knowledge representations, in mid‐stream take personalization further (French, Chapin, & Martin, 2004); such flexibility also introduces problems for systems designed to “know” what interface a user needs (Semeraro, Ferilli, Fanizzi, & Abbattista, 2001). Personalization features linked to artificial intelligence are said to enhance user profile‐driven filtering services (Gentili, Micarelli, & Sciarrone, 2003).…”

Section: Functionsmentioning

confidence: 99%

Digital libraries

Bearman¹

2007

Annual Review Info Sci & Tec

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Section: Functionsmentioning

confidence: 99%

Digital libraries

Bearman¹

2007

Annual Review Info Sci & Tec

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“…An example of adaptive interface personalization using the first approach is Fernandez, Diaz, & Aedo (1999), which provides adaptation of the interface at a very basic level depending on the operative system and the hardware and software platform. Semeraro et al, (1999) and Semeraro et al, (2001) present an example of adaptive interface personalization using a stereotype, in this case the level of tool expertise. The system, once a user has started a session, obtains the level of expertise of the user and provides him/her with the most relevant interface .…”

Section: Adaptive Interface Personalizationmentioning

confidence: 99%

Automated user modeling for personalized digital libraries

Frı́as-Martı́nez

Magoulas

Chen

et al. 2006

International Journal of Information Management

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Abstract.Digital libraries (DL) have become one of the most typical ways of accessing any kind of digitalized information. Due to this key role, users welcome any improvements on the services they receive from digital libraries. One trend used to improve digital services is through personalization. Up to now, the most common approach for personalization in digital libraries has been user-driven. Nevertheless, the design of efficient personalized services has to be done, at least in part, in an automatic way. In this context, machine learning techniques automate the process of constructing user models. This paper proposes a new approach to construct digital libraries that satisfy user's necessity for information: Adaptive Digital Libraries, libraries that automatically learn user preferences and goals and personalize their interaction using this information.

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“…In spite of the large amount of research work done by many researchers in the field of Private Information Retrieval [7], [8], [9], [10], [11], [12], [13] the most important question that has been raised is to reduce the communication complexity or exclude the preprocessing overload are still far from resolution. The burning problem is to understand whether PIR protocols involving constant number of servers require polynomial (or poly logarithmic) amount of communication.…”

Section: Literature Reviewmentioning

confidence: 99%

PIR with P-Cache: A New Private Information Retrieval Protocol With Improved Performance

Hoque

Hossain

2008

MJCS

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The increasing model of e-commerce infrastructure opens the door for secure transaction of information over the is introduced, based on the concept of database caching technology. In an average case, whenever a client requests a query in the system, there is a high probability to satisfy it from the P-cache instead of accessing the main database server that contains a huge amount of records. Our protocol outperforms the existing protocols in terms of both communication and computational complexity for queries supporting from P-cache and hence an improved performance.Keywords: PIR, P-cache, Database Caching, Hashing. INTRODUCTIONAs online transaction is increases day by day, the use of secured online software with database access and information retrieval is also ever-increasing. Private Information Retrieval (PIR), a protocol that allows the user to retrieve information from a database server while hiding the identity of the record retrieved by the user, meets the requirements of the next generation e-commerce applications. Some applications of the PIR are patent databases, pharmaceutical databases, media databases, digital library, e-voting system, ethical hacking, bioinformatics, secret sharing etc.It is a big challenge to create database with efficient PIR protocols that can ensure a good or at least acceptable response time. The main costs of PIR protocols are the communication and computational cost during query processing. A number of research works have been performed in recent years to reduce both the costs. Chor et al.[1] states two fundamental assumptions for PIR. Firstly, PIR is impossible unless we consider sending the entire database to the client as a solution; that is communication complexity is proven to the total size of the database. Secondly, in order to answer a query, the entire database must be read. In this case, the computational complexity is equal to the searching time on the whole database. On the other hand, it is a violation of user privacy if some records in the server are not read by client while processing.To solve the existing problems and to improve the performance of a PIR, the database caching technology is used in our proposed PIR with P-cache. Existing technology requires preprocessing and off-line communication to improve performance. The use of P-cache technology requires a little preprocessing and offline communication and achieves reasonable performance in most cases.

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Learning Interaction Models in a Digital Library Service

Cited by 15 publications

References 10 publications

Digital libraries

Digital libraries

Automated user modeling for personalized digital libraries

PIR with P-Cache: A New Private Information Retrieval Protocol With Improved Performance

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