Abstract Inductive Logic Programming (ILP) is a new discipline which investigates the inductive construction of first-order clausal theories from examples and background knowledge. We survey the most important theories and methods of this new field. First, various problem specifications of ILP are formalized in semantic settings for ILP, yielding a “model-theory” for ILP. Second, a generic ILP algorithm is presented. Third, the inference rules and corresponding operators used in ILP are presented, resulting in a “proof-theory” for ILP. Fourth, since inductive inference does not produce statements which are assured to follow from what is given, inductive inferences require an alternative form of justification. This can take the form of either probabilistic support or logical constraints on the hypothesis language. Information compression techniques used within ILP are presented within a unifying Bayesian approach to confirmation and corroboration of hypotheses. Also, different ways to constrain the hypothesis language or specify the declarative bias are presented. Fifth, some advanced topics in ILP are addressed. These include aspects of computational learning theory as applied to ILP, and the issue of predicate invention. Finally, we survey some applications and implementations of ILP. ILP applications fall under two different categories: first, scientific discovery and knowledge acquisition, and second, programming assistants.
The power of any kind of network approach lies in the ability to simplify a complex system so that one can better understand its function as a whole. Sometimes it is beneficial, however, to include more information than in a simple graph of only nodes and links. Adding information about times of interactions can make predictions and mechanistic understanding more accurate. The drawback, however, is that there are not so many methods available, partly because temporal networks is a relatively young field, partly because it is more difficult to develop such methods compared to for static networks. In this colloquium, we review the methods to analyze and model temporal networks and processes taking place on them, focusing mainly on the last three years. This includes the spreading of infectious disease, opinions, rumors, in social networks; information packets in computer networks; various types of signaling in biology, and more. We also discuss future directions.
We offer a comprehensive review of the theoretical underpinnings and existing empirical evidence in the implicit leadership and implicit followership theories domain. After briefly touching on the historical roots of information-processing approaches to leadership and leader categorization theory, we focus on current contextualized and dynamic perspectives. We specifically present neural network approaches and adaptive resonance processes that guide leadership perceptions. We further address measurement issues, emerging areas of study such as implicit leadership theories, and identity and cross-cultural issues. We offer specific avenues for future research in the form of a systematic list of unanswered research questions and further outline leadership development implications.
Addriani Sukma Melati, Deni Yanuar, Novi Susilawati
Informasi yang tersebar di platform media sosial berperan penting dalam membentuk persepsi dan pertimbangan individu, yang kemudian tercermin dalam keyakinan mengenai kredibilitas dan integritas merek, yang dapat memotivasi keputusan pembelian. Penelitian ini bertujuan untuk menguji pengaruh Electronic Word of Mouth (e-WOM) dan kepercayaan merek terhadap minat beli produk Somethinc, khususnya pada Generasi Z di Kota Banda Aceh. Berdasarkan teori reasoned action dari Icek Ajzen dan Martin Fishbein, penelitian ini menggunakan pendekatan kuantitatif dengan menyebarkan kuisioner melalui Google Form kepada 289 responden. Data dianalisis menggunakan uji regresi linier berganda dengan bantuan perangkat lunak SPSS. Hasil analisis data menunjukkan bahwa e-WOM dan kepercayaan merek secara signifikan mempengaruhi minat beli secara parsial dan simultan. Selain itu, nilai adjusted R square sebesar 0,554 yang menunjukkan bahwa variabel independen mempengaruhi variabel dependen sebesar 55,4%, sementara sisa 44,6% dipengaruhi oleh variabel lain. Dengan demikian, dapat disimpulkan bahwa e-WOM dan kepercayaan merek berpengaruh signifikan terhadap minat beli produk Somethinc di kalangan Generasi Z di Kota Banda Aceh.
The information shared on social media platforms plays an important role in shaping individuals' perceptions and considerations, which are then reflected in beliefs about a brand's credibility and integrity, potentially motivating purchasing decisions. This study aims to examine the influence of Electronic Word of Mouth (e-WOM) and brand trust on the purchase intention of Somethinc products, specifically among Generation Z in Banda Aceh. Based on the Reasoned Action Theory by Icek Ajzen and Martin Fishbein, this study adopts a quantitative approach by distributing questionnaires via Google Forms to 289 respondents. The data were analyzed using multiple linear regression with the aid of SPSS software. The results of data analysis indicate that e-WOM and brand trust significantly affect purchase intention both partially and simultaneously. Additionally, the adjusted R-square value of 0.554 shows that the independent variables explain 55.4% of the dependent variable, while the remaining 44.6% is influenced by other variables. Therefore, it can be concluded that e-WOM and brand trust significantly influence the purchase intention of Somethinc products among Generation Z in Banda Aceh.