International Journal of Collaborative Intelligence
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International Journal of Collaborative Intelligence (5 papers in press)
Some classical pattern recognition methods: a review by Zhifen Wang, Weikuan Jia Abstract: As a fundamental artificial intelligence, pattern recognition has been successfully applied in many fields. It has broad and far-reaching significance on the development of economy and the progress of science and technology. Firstly, the basic concepts, principles and methods related to pattern recognition are introduced, which contribute to further understanding of pattern recognition. Feature extraction and selection is the key step of pattern recognition, which aims mainly at low loss dimensionality reduction and provides good premise for recognition. Currently, feature reduction has become hot and difficult issues of pattern recognition, machine learning and data mining. Then, the common methods of pattern recognition are discussed in details. The key techniques such as algorithms of each method, parameter setting and assessment standards are discussed at the greatest extent. In addition, the newest development of all the methods is also discussed and primary evaluation of effect of the application is made. At last, the development trend and application prospects of pattern recognition are proposed. Keywords: pattern recognition; feature extraction; statistical analysis; fuzzy theory; bionic theory; neural network; synergetic recognition.
An improved user interest modeling by considering user social relationship by Yanru Wang Abstract: User interest modeling has always been an important direction in the research of microblog social network. In previous studies, people paid more attention to the expansion of tags from microblog short texts, but ignored the information contained in the relationship between users. We improved the user interest model based on multi-tag semantic correlation by considering user social relationship (MTSC-SR). This model is built on the basis of the previous improved microblog user-tag matrix and integrates the social similarity matrix of users. The construction of user social similarity matrix is used to represent the similarity of two users by considering the static and dynamic interest information of users. We verify the validity of our method through experiments, and the data set is captured by the open API. The results show that the proposed algorithm has good performance in extracting users' interest features. Keywords: User interest model; User-tag matrix; Microblog social network; Social similarity.
Defining a Continuum from Individual, to Swarm, to
Collective Intelligence, to General Collective Intelligence by Andy E. Williams Abstract: The concept of Collective Intelligence (CI) is distinguished from concept of a General Collective Intelligence or GCI in that CI addresses a specific range of problems and therefore has narrow problem-solving ability, while GCI can potentially address any problem and therefore has general problem-solving ability. General problem solving ability in groups has been represented by a general collective intelligence factor c defined in analogy with the individual intelligence factor g which measures IQ. While groups might have an innate general collective intelligence factor, GCI is a hypothetical platform that combines groups into a virtual collective cognition with a single well-defined thread of collective reasoning having general problem-solving ability, thereby creating an artificial c factor separate from the innate c factor. GCI also creates the opportunity to exponentially increase this c factor. This paper explores the differences between various forms of innate or artificial, as well as individual and group cognition. Keywords: General Collective Intelligence; Collective Intelligence.
Approximating an Artificial General Intelligence or a General Collective Intelligence by Andy E. Williams Abstract: Human-Centric Functional Modeling (HCFM) has recently been used to define a model of Artificial General Intelligence (AGI) believed to have the capacity for human-like general problem-solving ability (intelligence), as well as a model of General Collective Intelligence (GCI) with the potential to combine individuals into a single collective intelligence that might have exponentially greater general problem-solving ability than any individual in the group. This paper explores how a rudimentary AGI and a rudimentary GCI might be implemented through approximating the functions of each, in order to create systems that provide sufficient value to incentivize more sophisticated implementations to be developed over time. The purpose of this paper is to define such an approximation and to demonstrate its value. Keywords: General Collective Intelligence; collective intelligence; Artificial General Intelligence; Human-Centric Functional Modeling.
Multi-Criteria Fuzzy Approach to recommendation system based on a Social Trust Model. by Pardeep Kumar, Ajeet Kumar Abstract: Recommender systems have been researched in the extreme in recent years due to increasing numbers of e-commerce sites which has made the information overload.A recommender system aims to provide users with personalized online product or service recommendations to handle the increasing online information overload problem and improve customer relationship management.In general, users provide overall rating to items but recently rating on multiple characteristics of the items have been studied and is in the developing phase.So much research work have been made in the past to build a recommendation system focusing on the ratings of a single criterion. However, No work has been done which take into account multi criteria with user social trust score. This paper presents a novel recommendation system approach using social trust score and fuzzy based metaheuristic approach. This Hybrid recommendation method can improve the prediction quality of recommendation system. Keywords: Web Recommendation; Recommendation System; Fuzzy Multi-criteria; Fuzzy Linguistic; Decisiion Making.