Pisa, 19 February, CYCLADES The Personalization Service Fabrizio Sebastiani IEI-CNR (Italy)

Pisa, 19 February, Main goal The Personalization Service (PS) is responsible for allowing a user to interact with the system in a flexible and highly personalized way.

Pisa, 19 February, Personalization as a topic-driven activity Personalization is viewed as a content-based notion; i.e. the interaction with the user must take into account the users interests. The users interests are viewed as a hierarchically structured set of topics, each of which represents the users subjective view of a discipline which is of interest to her. Personalization is achieved by –Creating and maintaining a set of topic profiles (i.e. internal representations of topics) –Letting the information seeking/presenting behaviour of the system be influenced by these profiles.

Pisa, 19 February, User topics and community topics Topics (and their profiles) may belong to: –a particular user (user-specific topics). –a particular community (community-specific topics). Any user has a default subscription to the topics belonging to a community she is a member of, and may selectively cancel these subscriptions. The topics that pertain to a user are thus the union of –the topics that belong to the user as an individual –the topics that belong to the communities the user is a member of.

Pisa, 19 February, An example topic hierarchy Fuzzy Logic Possibilistic Logics Digital Libraries Probabilistic Logics Logics for Uncertainty and Imprecision Umbertos CYCLADES folder Information Retrieval Logics of subjective probability Logics of objective probability

Pisa, 19 February, Topic-based personalization Personalization influences the behaviour of the system in –Seeking information –Presenting the retrieved information to the user both when it operates –in ad hoc mode –in on-demand mode

Pisa, 19 February, Personalization in the ad hoc mode Ad hoc (pull) mode: the system delivers to the user information it deems relevant to a specific request she has just explicitly issued. This modality is apt to serve user information needs of a contingent (temporally local) nature. For personalization, the topic profiles of the user and of the communities to which the user belongs are to be used globally (thus forming a user profile) as "background information" that allow the request to be understood in the context of the users long-term interests.

Pisa, 19 February, Personalization in the on demand mode On demand mode: the user asks the system to deliver to her any information that might have recently become available and that is relevant to her own interests. This modality is used to satisfy information needs of a permanent or semi-permanent (temporally global) nature. For personalization, each of these profiles is to be used as a standing (i.e. permanent) query.

Pisa, 19 February, Classification of results The PS further provides personalized automatic classification of the records resulting from the (either ad hoc or on-demand) information-providing activity, into a set of hierarchically organized folders, each corresponding to a topic. A topic profile is thus (the declarative part of) a classifier, i.e. a tool that can automatically decide whether an item is relevant or not to the topic Any automatic classifier is going to have a non-null error rate: the user is thus allowed to correct the classifiers decisions that she perceives as wrong

Pisa, 19 February, How are classifiers built and updated? The classifier is automatically built by learning from items the user has classified manually. The classifier is automatically updated by interpreting implicit user feedback, consisting of –moving an item from folder A to folder B –deleting an item from folder A –aliasing an item from folder A to folder B Updates reflect –errors by the classifier –semantic shifts in the meaning of the involved topics

Pisa, 19 February, Dynamic topic hierarchies The user (or the community owner) may decide herself how to structure the topic hierarchy initially; a single-node hierarchy is the default The topic hierarchy is dynamic, as the user (or the system, after user approval) may restructure it by –Splitting a topic into several subtopics –Collapsing the subtopics into a single topic –Deleting a topic

Pisa, 19 February, Some technical issues Topic profiles will be inductively built and updated by supervised learning techniques; we plan to use incremental classification techniques (e.g. Balanced Winnow) The hierarchical topic structure will be dynamically modified by unsupervised learning techniques (i.e. clustering) The classifiers will be evaluated and optimized using user- dependent utility measures (e.g. giving different penalties to errors of commission and errors of omission).

Pisa, 19 February, The PS and the Mediator Service When the MS interacts with user X, the PS feeds to the MS the topic profiles (resp. user profile) of X that the QBS uses to issue on-demand X queries (resp. to personalize ad hoc X queries) The QBS feeds to the PS the results of these queries that the PS classifies in the topic hierarchy specific to the user. The MS informs the PS of user actions (such as moving, deleting or aliasing records across folders) that the PS may use for updating topic profiles and/or restructuring (upon user approval) the structure of the topic hierarchy.