The number of research papers available is growing at a staggering rate. Researchers need tools to help them find the papers they should read among all the papers published each year. In this paper, we present and experiment with hybrid recommender algorithms that combine Collaborative Filtering and Content-based Filtering to recommend research papers to users. Our hybrid algorithms combine the strengths of each filtering approach to address their individual weaknesses. We evaluated our algorithms through offline experiments on a database of 102,000 research papers, and through an online experiment with 110 users. For both experiments we used a dataset created from the CiteSeer repository of computer science research papers. We developed separate English and Portuguese versions of the interface and specifically recruited American and Brazilian users to test for cross-cultural effects. Our results show that users value paper recommendations, that the hybrid algorithms can be successfully combined, that different algorithms are more suitable for recommending different kinds of papers, and that users with different levels of experience perceive recommendations differently. These results can be applied to develop recommender systems for other types of digital libraries.

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a b s t r a c tThe working group Ontologies for Robotics and Automation, sponsored by the IEEE Robotics & Automation Society, recently proposed a Core Ontology for Robotics and Automation (CORA). This ontology was developed to provide an unambiguous definition of core notions of robotics and related topics. It is based on SUMO, a top-level ontology of general concepts, and on ISO 8373:2012 standard, developed by the ISO/TC184/SC2 Working Group, which defines-in natural language-important terms in the domain of Robotics and Automation (R&A). In this paper, we introduce a set of ontologies that complement CORA with notions such as industrial design and positioning. We also introduce updates to CORA in order to provide more ontologically sound representations of autonomy and of robot parts.

Abstract-Unambiguous definition of spatial position and orientation has crucial importance for robotics. In this paper we propose an ontology about positioning. It is part of a more extensive core ontology being developed by the IEEE RAS Working Group on ontologies for robotics and automation. The core ontology should provide a common ground for further ontology development in the field. We give a brief overview of concepts in the core ontology and then describe an integrated approach for representing quantitative and qualitative position information.

In this paper, we propose a cognitive semantic approach to represent part-whole relations. We base our proposal on the theory of conceptual spaces, focusing on prototypical structures in part-whole relations. Prototypical structures are not accounted for in traditional mereological formalisms. In our account, parts and wholes are represented in distinct conceptual spaces; parts are joined to form wholes in a structure space. The structure space allows systematic similarity judgments between wholes, taking into consideration shared parts and their configurations. A point in the structure space denotes a particular part structure; regions in the space represent different general types of part structures. We argue that the structural space can represent prototype effects: structural types are formed around typical arrangements of parts. We also show how structure space captures the variations in part structure of a given concept across different domains. In addition, we discuss how some taxonomies of part-whole relations can be understood within our framework.