An Improved Real-Time Recommendation for Microblogs Based on Topic

2019 ◽  
Vol 34 (02) ◽  
pp. 2059006
Author(s):  
Yikui Shi ◽  
Jiyan Liu ◽  
Lei Shi ◽  
Jianwen Zhao ◽  
Na Su
Keyword(s):  
Real Time ◽  
Information Overload ◽  
Rapid Development ◽  
Search Space ◽  
Decay Function ◽  
Recommendation Algorithm ◽  
User Similarity ◽  
User Clustering ◽  
Intermediate Variables ◽  
Over Time

With the rapid development of the Internet, people are confronted with information overload. Many recommendation methods are designed to solve this problem. The main contributions of recommendation methods proposed in this paper are as follows: (1) An improved collaborative filtering recommendation algorithm based on user clustering is proposed. Clustering is performed according to user similarity based on the user-item rating matrix. So the search space of recommendation algorithm is reduced. (2) Considering the factor that user’s interests may dynamically change over time, a time decay function is introduced. (3) A method of real-time recommendation based on topic for microblogs is designed to realize real-time recommendation effectively by preserving intermediate variables of user similarity. Experiments show that the proposed algorithms have been improved in terms of running time and accuracy.

Research on Location-Based Personalized Recommendation System

2014 ◽  
Vol 490-491 ◽  
pp. 1493-1496
Author(s):  
Huan Gao ◽  
Xi Tian ◽  
Xiang Ling Fu
Keyword(s):  
Collaborative Filtering ◽  
Real Time ◽  
Recommendation System ◽  
Information Overload ◽  
Information Filtering ◽  
Mobile Internet ◽  
Personalized Recommendation ◽  
Recommendation Algorithm ◽  
New System

With the mobile Internet developing in China, the problem of information overload has been brought to us. The traditional personalized recommendation cannot meet the needs of the mobile Internet. In this paper, the recommendation algorithm is mainly based on the collaborative filtering, but the new factors are introduced into the recommendation system. The new system takes the user's location and friends recommendation into the personalized recommendation system so that the recommendation system can meet the mobile Internet requirements. Besides, this paper also puts forward the concept of moving business circle for information filtering, which realizes the precise and real-time personalized recommendations. This paper also proves the recommendation effects through collecting and analyzing the data, which comes from the website of dianping.com.

scholarly journals Research of the Context Recommendation Algorithm Based on the Tripartite Graph Model in Complex Systems

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Fei Long
Keyword(s):  
Complex Systems ◽  
Information Overload ◽  
Rapid Development ◽  
Three Dimensional ◽  
Graph Model ◽  
Personalized Recommendation ◽  
Three Dimensional Model ◽  
Recommendation Algorithm ◽  
Tripartite Graph ◽  
Recommendation Algorithms

With the rapid development of information technology, the information overload has become a very serious problem in web information environment. The personalized recommendation came into being. Current recommending algorithms, however, are facing a series of challenges. To solve the problem of the complex context, a new context recommendation algorithm based on the tripartite graph model is proposed for the three-dimensional model in complex systems. Improving the accuracy of the recommendation by the material diffusion, through the heat conduction to improve the diversity of the recommended objects, and balancing the accuracy and diversity through the integration of resources thus realize the personalized recommendation. The experimental results show that the proposed context recommendation algorithm based on the tripartite graph model is superior to other traditional recommendation algorithms in recommendation performance.

scholarly journals A Recommendation Model for College Career Entrepreneurship Projects Based on Deep Learning

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yuan Feng ◽  
Weixian Huang
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Real Time ◽  
Deep Neural Network ◽  
Recommendation System ◽  
Information Overload ◽  
Matrix Decomposition ◽  
Recommendation Algorithm ◽  
Technology Platform ◽  
College Career

The recommendation system is an active, personalized, and real-time technology platform proposed in the 1990s to solve the problem of information overload. The recommendation system can constantly adjust the recommendation results according to the real-time behaviors of users. In other words, if the user’s interest changes, the recommendation system can present different information to the user. Therefore, the recommendation system is the best way to solve the problem of information overload in entrepreneurial projects. Based on the ConvMF algorithm, this paper proposes an entrepreneurial project recommendation algorithm based on a deep neural network and matrix decomposition. A deep neural network was established for the extraction of the hidden features of entrepreneurial projects, and a convolution neural network was used to process the text description information of entrepreneurial projects. One-hot coding was used to process the regional characteristics and financing round characteristics of entrepreneurial projects, and word embedding was used to process the label features of entrepreneurial projects. The implicit features of users are extracted from the user’s rating matrix using matrix decomposition technology. Finally, recommendations are made according to the implicit characteristics of users and the items learned.

A Collaborative Filtering Recommendation Method Based on Item Category

2012 ◽  
Vol 605-607 ◽  
pp. 2430-2433
Author(s):  
Wei Bin Deng ◽  
Jin Liu
Keyword(s):  
Collaborative Filtering ◽  
Real Time ◽  
Recommender System ◽  
Nearest Neighbors ◽  
Search Space ◽  
User Preferences ◽  
Experimental Results ◽  
Recommendation Algorithm ◽  
Search Speed ◽  
Speed And Accuracy

Traditional collaborative filtering algorithms are facing severe challenges of sparse user rating and real-time recommendation. To solve the problems, the category structure of merchandise is analyzed deeply and a collaborative filtering recommendation algorithm based on item category is proposed. A smooth filling technique is used for rating matrix with user preferences and all users rating on the item to solve the sparse problem. A user has different interests on different category. For every item, the nearest neighbors are searched within the category of the item. Not only is the search space of the users’ neighbors reduced greatly, but also search speed and accuracy are promoted. The experimental results show that the method can efficiently improve the recommendation scalability and accuracy of the recommender system.

Eternal Today

2018 ◽  
Author(s):  
Jenni Myllykoski ◽  
Anniina Rantakari
Keyword(s):  
Real Time ◽  
Constitutive Relation ◽  
Human Agency ◽  
Fundamental Characteristic ◽  
Time Study ◽  
Software Company ◽  
Present Experience ◽  
Managerial Strategy ◽  
Over Time ◽  
Strategy Making

This chapter focuses on temporality in managerial strategy making. It adopts an ‘in-time’ view to examine strategy making as the fluidity of the present experience and draws on a longitudinal, real-time study in a small Finnish software company. It shows five manifestations of ‘in-time’ processuality in strategy making, and identifies a temporality paradox that arises from the engagement of managers with two contradictory times: constructed linear ‘over time’ and experienced, becoming ‘in time’. These findings lead to the re-evaluation of the nature of intention in strategy making, and the authors elaborate the constitutive relation between time as ‘the passage of nature’ and human agency. Consequently, they argue that temporality should not be treated merely as an objective background or a subjective managerial orientation, but as a fundamental characteristic of processuality that defines the dynamics of strategy making.

Dynamic network intelligent hybrid recommendation algorithm and its application in online shopping platform

2021 ◽  
pp. 1-13
Author(s):  
Yuxuan Gao ◽  
Haiming Liang ◽  
Bingzhen Sun
Keyword(s):  
Online Shopping ◽  
Rapid Development ◽  
Dynamic Network ◽  
Topsis Method ◽  
Recommendation Algorithm ◽  
Time Periods ◽  
The Difference ◽  
Relationship Of ◽  
Hybrid Recommendation ◽  
Novel Model

With the rapid development of e-commerce, whether network intelligent recommendation can attract customers has become a measure of customer retention on online shopping platforms. In the literature about network intelligent recommendation, there are few studies that consider the difference preference of customers in different time periods. This paper proposes the dynamic network intelligent hybrid recommendation algorithm distinguishing time periods (DIHR), it is a integrated novel model combined with the DEMATEL and TOPSIS method to solved the problem of network intelligent recommendation considering time periods. The proposed method makes use of the DEMATEL method for evaluating the preference relationship of customers for indexes of merchandises, and adopt the TOPSIS method combined with intuitionistic fuzzy number (IFN) for assessing and ranking the merchandises according to the indexes. We specifically introduce the calculation steps of the proposed method, and then calculate its application in the online shopping platform.

Physical Aggression Is Associated With More Effective Postdecisional Processing of Social Threat

2021 ◽  
pp. 216770262096629
Author(s):  
Grace M. Brennan ◽  
Arielle Baskin-Sommers
Keyword(s):  
Real Time ◽  
Physical Aggression ◽  
Social Threat ◽  
Social Decisions ◽  
Angry Rumination ◽  
Incarcerated Men ◽  
Over Time

Physically aggressive individuals are more likely to decide that others are threatening. Yet no research has examined how physically aggressive individuals’ social decisions unfold in real time. Seventy-five incarcerated men completed a task in which they identified the emotions in faces displaying anger (i.e., threat) and happiness (i.e., nonthreat) at low, moderate, or high ambiguity. Participants then rated their confidence in their decisions either immediately or after a delay, and changes in confidence provided an index of postdecisional processing. Physical aggression was associated with stronger differentiation of threatening and nonthreatening faces under moderate ambiguity. Moreover, physical aggression was associated with steeper decreases in confidence over time following decisions that threatening faces were nonthreatening, indicating more extensive postdecisional processing. This pattern of postdecisional processing mediated the association between physical aggression and angry rumination. Findings suggest a role for postdecisional processing in the maintenance of threat-based social decisions in physical aggression.

scholarly journals Module to Support Real-Time Microscopic Imaging of Living Organisms on Ground-Based Microgravity Analogs

2021 ◽  
Vol 11 (7) ◽  
pp. 3122
Author(s):  
Srujana Neelam ◽  
Audrey Lee ◽  
Michael A. Lane ◽  
Ceasar Udave ◽  
Howard G. Levine ◽  
...  
Keyword(s):  
Real Time ◽  
High Speed ◽  
Simulated Microgravity ◽  
Image Acquisition ◽  
Time Lapse ◽  
Moving Frames ◽  
Cell Functions ◽  
Microgravity Simulation ◽  
Division Cell ◽  
Over Time

Since opportunities for spaceflight experiments are scarce, ground-based microgravity simulation devices (MSDs) offer accessible and economical alternatives for gravitational biology studies. Among the MSDs, the random positioning machine (RPM) provides simulated microgravity conditions on the ground by randomizing rotating biological samples in two axes to distribute the Earth’s gravity vector in all directions over time. Real-time microscopy and image acquisition during microgravity simulation are of particular interest to enable the study of how basic cell functions, such as division, migration, and proliferation, progress under altered gravity conditions. However, these capabilities have been difficult to implement due to the constantly moving frames of the RPM as well as mechanical noise. Therefore, we developed an image acquisition module that can be mounted on an RPM to capture live images over time while the specimen is in the simulated microgravity (SMG) environment. This module integrates a digital microscope with a magnification range of 20× to 700×, a high-speed data transmission adaptor for the wireless streaming of time-lapse images, and a backlight illuminator to view the sample under brightfield and darkfield modes. With this module, we successfully demonstrated the real-time imaging of human cells cultured on an RPM in brightfield, lasting up to 80 h, and also visualized them in green fluorescent channel. This module was successful in monitoring cell morphology and in quantifying the rate of cell division, cell migration, and wound healing in SMG. It can be easily modified to study the response of other biological specimens to SMG.

scholarly journals Phone-Based Restaurant Recommendation System by Using Position Information and Association Rules

2012 ◽  
Vol 6-7 ◽  
pp. 783-789
Author(s):  
Jian Feng Dong ◽  
Tian Yang Dong ◽  
Jia Jie Yao ◽  
Ling Zhang
Keyword(s):  
Mobile Phone ◽  
Real Time ◽  
Association Rules ◽  
Recommendation System ◽  
Rapid Development ◽  
Smart Phone ◽  
Smart Phones ◽  
Location Information ◽  
Position Information ◽  
The Real

With the rapid development of smart-phone applications, how to make the ordering process via smart-phones more convenient and intelligent has become a hotspot. This paper puts forward a method of restaurant dish recommendation relying on position information and association rules. In addition, this paper has designed and developed a restaurant recommendation system based on mobile phone. The system would fetch the real-time location information via smart-phones, and provide customers personalized restaurant and dish recommendation service. According to the related applications, this system can successfully recommend the related restaurants and food information to customers.

scholarly journals Digital nanophotonics: the highway to the integration of subwavelength-scale photonics

Nanophotonics ◽  
2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Jie Huang ◽  
Hansi Ma ◽  
Dingbo Chen ◽  
Huan Yuan ◽  
Jinping Zhang ◽  
...  
Keyword(s):  
Rapid Development ◽  
Search Space ◽  
Inverse Design ◽  
Analytical Models ◽  
Nanophotonic Devices ◽  
Single Function ◽  
Intelligence Operations ◽  
Complex Functions ◽  
Parameter Search Space ◽  
Design Algorithms

AbstractNanophotonic devices with high densities are extremely attractive because they can potentially merge photonics and electronics at the nanoscale. However, traditional integrated photonic circuits are designed primarily by manually selecting parameters or employing semi-analytical models. Limited by the small parameter search space, the designed nanophotonic devices generally have a single function, and the footprints reach hundreds of microns. Recently, novel ultra-compact nanophotonic devices with digital structures were proposed. By applying inverse design algorithms, which can search the full parameter space, the proposed devices show extremely compact footprints of a few microns. The results from many groups imply that digital nanophotonics can achieve not only ultra-compact single-function devices but also miniaturized multi-function devices and complex functions such as artificial intelligence operations at the nanoscale. Furthermore, to balance the performance and fabrication tolerances of such devices, researchers have developed various solutions, such as adding regularization constraints to digital structures. We believe that with the rapid development of inverse design algorithms and continuous improvements to the nanofabrication process, digital nanophotonics will play a key role in promoting the performance of nanophotonic integration. In this review, we uncover the exciting developments and challenges in this field, analyse and explore potential solutions to these challenges and provide comments on future directions in this field.

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