Predictions of missing links of incomplete networks like protein-protein interaction networks or very likely but not yet existent links in evolutionary networks like friendship networks in web society can be considered as a guideline for further experiments or valuable information for web users. In this paper, we introduce a local path index to estimate the likelihood of the existence of a link between two nodes. We propose a network model with controllable density and noise strength in generating links, as well as collect data of six real networks. Extensive numerical simulations on both modeled networks and real networks demonstrated the high effectiveness and efficiency of the local path index compared with two well-known and widely used indices, the common neighbors and the Katz index. Indeed, the local path index provides competitively accurate predictions as the Katz index while requires much less CPU time and memory space, which is therefore a strong candidate for potential practical applications in data mining of huge-size networks.

We introduce a simple model to study movie competition in the recommender systems. Movies of heterogeneous quality compete against each other through viewers' reviews and generate interesting dynamics of box-office. By assuming mean-field interactions between the competing movies, we show that run-away effect of popularity spreading is triggered by defeating the average review score, leading to hits in box-office. The average review score thus characterizes the critical movie quality necessary for transition from box-office bombs to blockbusters. The major factors affecting the critical review score are examined. By iterating the mean-field dynamical equations, we obtain qualitative agreements with simulations and real systems in the dynamical forms of box-office, revealing the significant role of competition in understanding box-office dynamics.

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 number of channels being equal to the number of different ratings. Each channel represents a certain rating and a user having voted an object will be connected to the channel corresponding to the rating. Diffusion process taking place on such a user-channel bipartite graph gives a new similarity measure of user pairs, which is further demonstrated to be more accurate than the classical Pearson correlation coefficient under the standard collaborative filtering framework.

In this paper, we propose a novel recommendation algorithm fusing the opinions from experts and ordinary people. Instead of regarding one's judgement capability as his/her expertise, we present a new definition which measures the amount of the recommendable items one know in a certain area. When computing the expertise, we consider both the average value and the accumulative value, and introduce a free parameter α to tune between these two values. To evaluate the proposed algorithm, simulations are run on the Moviepilot dataset, and the results demonstrate that our algorithm outperforms the conventional collaborative filtering algorithm.

A101be seen as blocking access. As the marginal cost (MC) of a new product is lower than the charged price there is a well-known waste. One option is to establish a two-part pricing model with a "subscription" price plus a usage price close to MC. The objective of this paper is to provide an economic analysis based on theories and concepts from microeconomics and industrial organization of two-part pricing in the market for patent protected medicines (PPM). Methods: The situation will be analyzed from a game theoretical and an empirical perspective. The starting point is the Swedish Health Care system with focus on oncology. A two-part pricing contractual arrangement will also be discussed for some other EU countries. Results: Demand side consists of a publicly funded local buyer who represents a large number of potential users. This often leads to a bargaining solution where price is below the one set by a standard monopoly. A two-part pricing -where the buyer pays a substantial fixed-fee to get access to the PPM and a per unit price equal to marginal cost -may increase efficiency. However, numerous issues need to be taken into account when considering introducing two-part pricing, for example uncertainty and risk, the operation on many markets, free-riders and reselling. ConClusions: Quantities are unlikely to be efficient with the current pricing model in the Swedish oncological market. A twopart pricing is likely to increase the efficiency in such markets but is also associated with some serious challenges.