Joint Representation Learning of Cross-lingual Words and Entities via Attentive Distant Supervision

Joint representation learning of words and entities benefits many NLP tasks, but has not been well explored in cross-lingual settings. In this paper, we propose a novel method for joint representation learning of cross-lingual words and entities. It captures mutually complementary knowledge, and enables cross-lingual inferences among knowledge bases and texts. Our method does not require parallel corpora, and automatically generates comparable data via distant supervision using multi-lingual knowledge bases. We utilize two types of regularizers to align cross-lingual words and entities, and design knowledge attention and cross-lingual attention to further reduce noises. We conducted a series of experiments on three tasks: word translation, entity relatedness, and cross-lingual entity linking. The results, both qualitatively and quantitatively, demonstrate the significance of our method.Comment: 11 pages, EMNLP201

Recognizing Variable Environments: The Theory of Cognitive Prism

Normal adults do not have any difficulty in recognizing their homes. But can artificial systems do in the same way as humans? This book collects interdisciplinary evidences and presents an answer from the perspective of computing, namely, the theory of cognitive prism. To recognize an environment, an intelligent system only needs to classify objects, structures them based on the connection relation (not through measuring!), subjectively orders the objects, and compares with the target environment, whose knowledge is similarly structured. The intelligent system works, therefore, like a prism: when a beam of light (a scene) reaches (is perceived) to an optical prism (by an intelligent system), some light (objects) is reflected (are neglected), those passed through (the recognized objects) are distorted (are ordered differently). So comes the term 'cognitive prism'! Two fundamental propositions used in the theory can be informally stated as follow: an orientation relation is a kind of distance comparison relation -- you being in front of me means you being nearer to my face than to my other sides; a pair of objects being connected means any object, precisely the space occupied by the object, can be moved to a place where it connects with the pair

Recognizing variable spatial environments--The theory of cognitive prism

Objects are not statically located in environments. Therefore, a snapshot view of an environment at one moment may be quite different from its snapshot at other moments. However, people are capable of recognizing the environment. This thesis presents a theory of recognizing variable spatial environments -- The Theory of Cognitive Prism. It collected theoretical and empirical evidences from several disciplines, such as cognitive psychology, neurology, psycho-linguistics, philosophy, and proposes a symbolic computational theory. This thesis has three parts: The first part is the description of the theory in natural language. It presents a commonsense knowledge of the snapshot view of a spatial environment -- the cognitive spectrum , and of the process of recognizing a spatial environment by comparing two cognitive spectrums. The second part is the mereotopological formalism of the theory. It presents the formal structure of the cognitive spectrum and the process of comparing two formalized cognitive spectrums. The third part introduces a symbolic simulating system of the theory -- the LIVE model.The research questions are: (1) What are the spatial relations between extended objects through observation? (2) According to what principle is the reference orderingbetween extended objects formed? (3) What is the structure of a cognitive spectrum? (4) How shall two cognitive spectrums be compared? (5) How does the differencebetween two cognitive spectrums determine the degree of the compatibility between the perceived cognitive spectrum and the target one? (6) How shall the results of Question (1) to (5) be formalized? Distance relations between extended objects are understood by the degree of the extension from one extended object to the other; orientation relations between two extendedobjects are distance comparison between one extended object and sides of the other extended object. The reference ordering between two extended objects is based on the commonsense knowledge of relative stabilities of related objects. The cognitive spectrum is structured by extended objects and their spatial relations which obey the reference ordering. Two cognitive spectrums are compared based on the categories and locations of extended objects. The compatibility of two cognitive spectrums is determined by their differences and relative stabilities of related objects. Recognizing spatial environments is the comparison process between the cognitive spectrum of the perceived environment and the cognitive spectrum of target environment and the judgement of the compatibility between them. All above are mereotopolgically formalized by the connectedness relationship C. The computational complexity of the formalized recognition process is polynomial P. A symbolic simulation system, the LIVE model, has been implemented in Lisp

Erkennen variabler räumlicher Umgebungen--Die Theorie des Kognitiven Prismas

Objects are not statically located in environments. Therefore, a snapshot view of an environment at one moment may be quite different from its snapshot at other moments. However, people are capable of recognizing the environment. This thesis presents a theory of recognizing variable spatial environments -- The Theory of Cognitive Prism. It collected theoretical and empirical evidences from several disciplines, such as cognitive psychology, neurology, psycho-linguistics, philosophy, and proposes a symbolic computational theory. This thesis has three parts: The first part is the description of the theory in natural language. It presents a commonsense knowledge of the snapshot view of a spatial environment -- the "cognitive spectrum", and of the process of recognizing a spatial environment by comparing two cognitive spectrums. The second part is the mereotopological formalism of the theory. It presents the formal structure of the cognitive spectrum and the process of comparing two formalized cognitive spectrums. The third part introduces a symbolic simulating system of the theory -- the LIVE model.The research questions are: (1) What are the spatial relations between extended objects through observation? (2) According to what principle is the reference orderingbetween extended objects formed? (3) What is the structure of a cognitive spectrum? (4) How shall two cognitive spectrums be compared? (5) How does the differencebetween two cognitive spectrums determine the degree of the compatibility between the perceived cognitive spectrum and the target one? (6) How shall the results of Question (1) to (5) be formalized? Distance relations between extended objects are understood by the degree of the extension from one extended object to the other; orientation relations between two extendedobjects are distance comparison between one extended object and sides of the other extended object. The reference ordering between two extended objects is based on the commonsense knowledge of relative stabilities of related objects. The cognitive spectrum is structured by extended objects and their spatial relations which obey the reference ordering. Two cognitive spectrums are compared based on the categories and locations of extended objects. The compatibility of two cognitive spectrums is determined by their differences and relative stabilities of related objects. Recognizing spatial environments is the comparison process between the cognitive spectrum of the perceived environment and the cognitive spectrum of target environment and the judgement of the compatibility between them. All above are mereotopolgically formalized by the connectedness relationship C. The computational complexity of the formalized recognition process is polynomial P. A symbolic simulation system, the LIVE model, has been implemented in Lisp

An Object-Oriented Design of a Multimedia Item Pool

An item pool with multimedia data is a finclamental part of our project? Computerized Adaptive Test System of Chinese Proficiency. This pper intends to present a design of a multimedia item pool from an object-oriented perspective. It is stressed that 00 approach is especially esfective in modeling and managing complex multimedia data. We first introduce our system architecture using 00-layer method Multimedia data organization of the database is investigated and detailed class definition is given next. The object-oriented SQL-like syntax ofthe query language is also simply described. 1

OpenBudgets.eu: A Distributed Open-Platform for Managing Heterogeneous Budget Data

OpenBudgets.eu (OBEU) provides an open-source software framework and accompanying Software-As-A-Service (SAAS) platform for supporting financial transparency, thus enhancing accountability within public sectors as well as influencing corruption prevention. To this end, a scalable framework for multi-stakeholders is developed, with the aim of maximizing flexibility and ease of use. The core features of the OBEU platform are: (1) A semantic data model used to integrate heterogenous budget data, giving a pre-defined structure to the input data; (2) a library of visualisation tools with a user-friendly interface, which enables stakeholders to visualise available data in different granularity and modality; (3) a library of data mining and comparative analysis tools, which enables the aggregation of existing data in order to obtain new outcomes and discover recent trends and patterns, and potentially forecasting budget measures; and (4) an interface for feedback and citizen engagement which enables users to evaluate, discuss and give feedback on the provided data. A demonstration of the OBEU platform and portal is available at http://apps.openbudgets.eu/ and can be easily embedded into municipalities’ websites

Structure and Learning (Dagstuhl Seminar 21362)

This report documents the program and the outcomes of Dagstuhl Seminar 21362 "Structure and Learning", held from September 5 to 10, 2021. Structure and learning are among the most prominent topics in Artificial Intelligence (AI) today. Integrating symbolic and numeric inference was set as one of the next open AI problems at the Townhall meeting "A 20 Year Roadmap for AI" at AAAI 2019. In this Dagstuhl seminar, we discussed related problems from an interdiscplinary perspective, in particular, Cognitive Science, Cognitive Psychology, Physics, Computational Humor, Linguistic, Machine Learning, and AI. This report overviews presentations and working groups during the seminar, and lists two open problems