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                <term xml:lang="en">information access</term>
                <term xml:lang="fr">accès à l'information</term>
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              <p>In many domains where information access plays  a central role, there is a gap between expert users who can ask  complex questions through formal query languages (e.g., SQL), and  lay users who either are dependent on expert users, or must restrict  themselves to ask simpler questions (e.g., keyword search).  Because  of the formal nature of those languages, there seems to be an  unescapable trade-off between expressivity and usability in  information systems. The objective of this thesis is to present a  number of results and perspectives that show that the expressivity  of formal languages can be reconciled with the usability of  widespread information systems (e.g., browsing, Faceted Search  (FS)). The final aim of this work is to empower people with the  capability to produce, explore, and analyze their data in a powerful  way.  We have proposed a number of theories and implementations to better  reconcile expressivity and usability, and applied them to a number  of contexts going from file systems to the Semantic Web. In this  thesis, we introduce an unifying framework inspired by Formal  Concept Analysis (FCA) to factor out the main ideas of all those  results: Abstract Conceptual Navigation (ACN). The principle of ACN  is to guide users by letting them navigate in a conceptual  space where places are concepts connected by navigation  links. Concepts are characterized by a formal query, and are made of  two parts: an extension and an intension. The extension  is made of query results while the intension is made of the query  itself and an index of query increments over results. Finally,  navigation links are formally defined as query transformations. The  conceptual space is not static but is induced by concrete data, and  evolves with it. ACN therefore combines the expressivity of  formal query languages with the guidance of conceptual  navigation. The readability of queries is improved by  verbalizing them to (or parsing them from) a Controlled Natural  Language (CNL). Readability and guidance together support usability  by speaking user's language, and by providing a systematic  assistance.</p>
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