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Optimal patentability requirements with fragmented property rights

Denicolò, Vincenzo; Halmenschlager, Christine - 2010

We study the effect of the fragmentation of intellectual property rights on optimal patent design. The major finding is … requirements should be stronger than in the case of stand-alone innovation. This reduces the fragmentation of intellectual property …

Persistent link: https://www.econbiz.de/10010272448

Will the Global Village Fracture into Tribes : Recommender Systems and Their Effects on Consumers

Hosanagar, Kartik; Fleder, Daniel M.; Lee, Dokyun; … - 2015

Personalization is becoming ubiquitous on the World Wide Web. Such systems use statistical techniques to infer a … emerged as to whether personalization has drawbacks. By making the web hyper-specific to our interests, does it fragment … internet users, reducing shared experiences and narrowing media consumption? We study whether personalization is in fact …

Persistent link: https://www.econbiz.de/10014046953

Information filtering via collaborative user clustering modeling

Zhang, Chu-Xu; Zhang, Zi-Ke; Yu, Lu; Liu, Chuang; Liu, Hao - In: Physica A: Statistical Mechanics and its Applications 396 (2014) C, pp. 195-203

The past few years have witnessed the great success of recommender systems, which can significantly help users to find out personalized items for them from the information era. One of the widest applied recommendation methods is the Matrix Factorization (MF). However, most of the researches on...

Persistent link: https://www.econbiz.de/10010730333

A pattern mining approach to enhance the accuracy of collaborative filtering in sparse data domains

Ramezani, Mohsen; Moradi, Parham; Akhlaghian, Fardin - In: Physica A: Statistical Mechanics and its Applications 408 (2014) C, pp. 72-84

Recommender systems seek to find the interesting items by filtering out the worthless items. Collaborative filtering is one of the most successful recommendation approaches. It typically associates a user with a group of like-minded users based on their preferences over all the items and...

Persistent link: https://www.econbiz.de/10010872047

Website-oriented recommendation based on heat spreading and tag-aware collaborative filtering

Zhang, Zi-Ke; Yu, Lu; Fang, Kuan; You, Zhi-Qiang; Liu, … - In: Physica A: Statistical Mechanics and its Applications 399 (2014) C, pp. 82-88

Recently, Recommender Systems has been widely applied in helping users find potentially interesting items from the era of big data. However, most of researches on this topic have focused on estimating the direct relationships between users and items, neglecting other available information. In...

Persistent link: https://www.econbiz.de/10010744292

Collaborative filtering with diffusion-based similarity on tripartite graphs

Shang, Ming-Sheng; Zhang, Zi-Ke; Zhou, Tao; Zhang, Yi-Cheng - In: Physica A: Statistical Mechanics and its Applications 389 (2010) 6, pp. 1259-1264

Collaborative tags are playing a more and more important role for the organization of information systems. In this paper, we study a personalized recommendation model making use of the ternary relations among users, objects and tags. We propose a measure of user similarity based on his...

Persistent link: https://www.econbiz.de/10010589156

Collaborative filtering based on multi-channel diffusion

Shang, Ming-Sheng; Jin, Ci-Hang; Zhou, Tao; Zhang, Yi-Cheng - In: Physica A: Statistical Mechanics and its Applications 388 (2009) 23, pp. 4867-4871

In this paper, by applying a diffusion process, we propose a new index to quantify the similarity between two users in a user–object bipartite graph. To deal with the discrete ratings on objects, we use a multi-channel representation where each object is mapped to several channels with the...

Persistent link: https://www.econbiz.de/10010591705

Analyzing Consumer-Product Graphs: Empirical Findings and Applications in Recommender Systems

Huang, Zan; Zeng, Daniel D.; Chen, Hsinchun - In: Management Science 53 (2007) 7, pp. 1146-1164

We apply random graph modeling methodology to analyze bipartite consumer-product graphs that represent sales transactions to better understand consumer purchase behavior in e-commerce settings. Based on two real-world e-commerce data sets, we found that such graphs demonstrate topological...

Persistent link: https://www.econbiz.de/10009191395

Toward Social-Semantic Recommender Systems

Sulieman, Dalia; Malek, Maria; Kadima, Hubert; Laurent, … - In: International Journal of Information Systems and Social … 7 (2016) 1, pp. 1-30

In this article, the authors consider the basic problem of recommender systems that is identifying a set of users to whom a given item is to be recommended. In practice recommender systems are run against huge sets of users, and the problem is then to avoid scanning the whole user set in order...

Persistent link: https://www.econbiz.de/10012045730

Using Social Tags and User Rating Patterns for Collaborative Filtering

Kim, Iljoo; Gupta, Vipul - In: International Journal of Information Systems and Social … 8 (2017) 2, pp. 25-49

The overwhelming supply of online information on the Web makes finding better ways to separate important information from the noisy data ever more important. Recommender systems may help users deal with the information overloading issue, yet their performance appears to have stalled in currently...

Persistent link: https://www.econbiz.de/10012045752