Recommending Products using Preference Based Modeling
نویسندگان
چکیده
Common approaches to product recommendations are offer level propensity models and collaborative filtering. These methods are typically used for respectively a low or a high number of products, and come with specific limitations. In this paper we introduce preference based approaches to product recommendations, aimed at filling the gap between these methods. This approach can be used for any expected value decision problem, with choices across alternatives with common sets of attributes.
منابع مشابه
A Review of Spatial Factor Modeling Techniques in Recommending Point of Interest Using Location-based Social Network Information
The rapid growth of mobile phone technology and its combination with various technologies like GPS has added location context to social networks and has led to the formation of location-based social networks. In social networking sites, recommender systems are used to recommend points of interest (POIs) to users. Traditional recommender systems, such as film and book recommendations, have a lon...
متن کاملPreference Aggregation in Group and Social Recommender Systems
Aggregating preference and recommending a common set of items for a group has become a challenging topic in recommender systems and social web sites. This issue is mainly concerned with eliciting individual users’ preferences, suggesting the maximized overall satisfaction outcome for all users and ensuring that the aggregation mechanism is resistant to manipulation. In the following we survey p...
متن کاملComprehensive Decision Modeling of Reverse Logistics System: A Multi-criteria Decision Making Model by using Hybrid Evidential Reasoning Approach and TOPSIS (TECHNICAL NOTE)
In the last two decades, product recovery systems have received increasing attention due to several reasons such as new governmental regulations and economic advantages. One of the most important activities of these systems is to assign returned products to suitable reverse manufacturing alternatives. Uncertainty of returned products in terms of quantity, quality, and time complicates the decis...
متن کاملRecommending Products When Consumers Learn Their Preferences
Consumers often learn their preferences as they search. For example, after test driving new cars, a consumer might find she undervalued trunk space and overvalued sunroofs. Preference learning makes search complex because, each time a product is searched, updated preferences affect the value of all products and the value of subsequent (optimal) search. Recommendations that take preference learn...
متن کاملRecommender Systems for Product Bundling
Recommender systems (RSs) enhance e-commerce sales by recommending relevant products to their customers. RSs aim at implementing the firm's web-based marketing strategy to increase revenues. Generating bundles is an example of a marketing strategy that aims to satisfy consumer needs and preferences, and at the same time, to increase customers' buying scope and the firm's income. Thus, finding a...
متن کامل