Adaptive Hypermedia Meets Provenance Evgeny Knutov Paul De Bra Mykola Pechenizkiy GAF project: Generic Adaptation Framework (project is supported byNWO (project is supported by NWO)

Agenda: Adaptive Hypermedia classification and Adaptation process GAF generic adaptation framework (layered model) Provenance modeling (W7) GAF sequence chart, key elements AH model meets Provenance model Issues and Prospective Solutions Conclusions / Department of Computer Science PAGE

Motivating examples: / Department of Computer Science PAGE

Classification of AH methods and techniques; adaptation process highlights: / Department of Computer Science PAGE Classification of AH methods and techniques integrated with adaptation process Basis for the AHS layered structure

GAF layered model: / Department of Computer Science PAGE GAF aligns the order of the layers in the system according to the classification of AH methods and techniques Rotate layered structure of GAF and match with adaptation process flowcharts GAF layered structure

W7 Provenance model: / Department of Computer Science PAGE W7 provenance model (S. Ram) Provenance is information about the origin, ownership, source, history, lineage and/or derivation of an information object or data

Adaptation process: Generic representation of the process Aligned it with the traditional ‘adaptation questions’ Align the layers of AHS in a sequence chart Matched flow and sequence process charts Reference Adaptation Process Aligned with the Provenance Model / Department of Computer Science PAGE 603/07/2015

GAF “sequence chart”: / Department of Computer Science PAGE

Key elements of GAF sequence chart: Layered structure preserved in a “sequence” Layers aligned with adaptation/provenance questions Layers aligned with process and flowchart Layers determine (de) composition of the GAF model / Department of Computer Science PAGE

AH meets Provenance: determine adaptationAdaptation: provenance data is used by AE to determine adaptation steps explaining adaptationExplanation: explaining system usage and adaptation origin AnalysisUsage pattern Analysis ReliabilityReliability of the AH system Semantics: expanding the description of the data to what is answered by the question Process and Pipeline centric provenance for Adaptation process / Department of Computer Science PAGE

AH meets Provenance (cont.): Question AHSProvenance model Why? stating the adaptation goal(s) (might be a domain concept, representing either a new goal to follow or a sequence of concepts) the set of reasons for triggering a particular event (evidence of what has happened) How? describing AH methods and techniques on a conceptual and implementation level (Adaptive Engine (AE) functionality); explains the sequence of event- actions; describes the semantics of cause-effect relations the set of all actions leading up to the events (keeping track of the events, and corresponding action in the system); describes the syntax of events and actions recorded / Department of Computer Science PAGE

Provenance Issues and Prospective Solutions: Harvesting issues GAF distinguishes AH layers, questions and data Understanding the semantics of provenance Matched AH and provenance question Diversity of data types and many places of origin GAF structure and process (de)composition Storing, Retrieving and Analysis Facilitated by versioning techniques in AH / Department of Computer Science PAGE

Conclusions: AHS provenance modeling (complimentary features description) Provide richer User experience, more sophisticated adaptation and recommendation techniques based on the data provenance information Conformity of the adaptation process and provenance model Layered process-based (de)composition of an adaptive system Building Block of a User-Adaptive System process / Department of Computer Science PAGE

Further work: Elaborate process description and extend generic adaptation process emphasizing particular use- cases and examples of provenance in AH Align adaptation sequence chart with other user- adaptive systems (e.g. Recommender systems, Adaptive Web search), show Emphasize interoperability of the AH developments in the context of provenance (e.g. open corpus adaptation, higher order adaptation, etc.) / Department of Computer Science PAGE

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AHS evolution: / Department of Computer Science PAGE Generalize AHS functionality in GAF Enhance GAF layered structure with the process Generalize adaptation process in GAF

Use-case: WWW Search sequence chart: / Department of Computer Science PAGE

Use-case: WWW Search: Sequence chart (GAP) compliance with the search process: Goal Model – defines search query Domain Model – defines search index Resource model - WWW Context Models – defines user and usage context properties (IP, user profile, etc.) Group Model – defines user collaborative profile Adaptation and Application models – define search engine and ranking mechanisms / Department of Computer Science PAGE