Efficient Computation of Range Aggregates against Uncertain
... θ within the distance γ to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to effectively and efficiently remove data points from verification. Our comprehensive experiments b ...
... θ within the distance γ to p. We propose novel, efficient techniques to solve the problem following the filtering-and-verification paradigm. In particular, two novel filtering techniques are proposed to effectively and efficiently remove data points from verification. Our comprehensive experiments b ...
Amazon.com recommendations item-to
... purchased it. Using collaborative filtering to generate recommendations is computationally expensive. It is O(MN) in the worst case, where M is the number of customers and N is the number of product catalog items, since it examines M customers and up to N items for each customer. However, because th ...
... purchased it. Using collaborative filtering to generate recommendations is computationally expensive. It is O(MN) in the worst case, where M is the number of customers and N is the number of product catalog items, since it examines M customers and up to N items for each customer. However, because th ...
E-Commerce Recommender Applications
... transactions to medical diagnosis to intrusion detection. Basu et al. (1998) built a hybrid recommender system that mixes collaborative and content filtering using an induction-learning classifier. Good et al. (1999) implemented induction-learned featurevector classification of movies and compared t ...
... transactions to medical diagnosis to intrusion detection. Basu et al. (1998) built a hybrid recommender system that mixes collaborative and content filtering using an induction-learning classifier. Good et al. (1999) implemented induction-learned featurevector classification of movies and compared t ...
INTELLIGENT TECHNIQUES FOR E
... CBR approach: CBR is a problem solving approach based on past experience. Past experience is organized in the form of cases, and is used to solve new problems [Prasad 1995]. Doctors, chefs, and lawyers are examples of case-based problem solvers because they use past cases in solving new problems. In ...
... CBR approach: CBR is a problem solving approach based on past experience. Past experience is organized in the form of cases, and is used to solve new problems [Prasad 1995]. Doctors, chefs, and lawyers are examples of case-based problem solvers because they use past cases in solving new problems. In ...
Ultimate Location In..
... in the filtering phase, effective and efficient filtering techniques will be applied to prune or validate the points. The algorithm consists of two phases. In the filtering phase for each entry e of RS to be processed, we do not need to further process e if it is pruned or validated by the filter F. ...
... in the filtering phase, effective and efficient filtering techniques will be applied to prune or validate the points. The algorithm consists of two phases. In the filtering phase for each entry e of RS to be processed, we do not need to further process e if it is pruned or validated by the filter F. ...
Slide 1
... Each hash bucket corresponds to a cluster, that puts two users together in the same cluster with probability equal to their item-set overlap similarity S( ui, uj ). Randomly permute a set of items(S) and for each user uu, compute its hash value h(u) as the index of the first item under the permutati ...
... Each hash bucket corresponds to a cluster, that puts two users together in the same cluster with probability equal to their item-set overlap similarity S( ui, uj ). Randomly permute a set of items(S) and for each user uu, compute its hash value h(u) as the index of the first item under the permutati ...
Document
... immensely to large volumes of real-world data on social behaviors. • Recognizing anonymous, yet identical users among multiple SMNs is still an intractable problem . Moreover, since online SMNs are quite symmetric, existing user identification schemes based on network structure are not effective . • ...
... immensely to large volumes of real-world data on social behaviors. • Recognizing anonymous, yet identical users among multiple SMNs is still an intractable problem . Moreover, since online SMNs are quite symmetric, existing user identification schemes based on network structure are not effective . • ...
Resto – Restaurant Menu Helper
... • Number of Participants – 33 • Target population- Indian Students studying at University of Florida – Frequently visit fast food restaurants around the campus – Face difficulty with names and pronunciations of food items ...
... • Number of Participants – 33 • Target population- Indian Students studying at University of Florida – Frequently visit fast food restaurants around the campus – Face difficulty with names and pronunciations of food items ...
Research proposal - University of South Australia
... et al. 1994). User who care about net news will need to rate the news based on certain aspects. Based on the rate from other user, the system can predict what the current user wants. The advance feature of the system including, openness, ease to use, compatibility, scalability and privacy. 2.2 Relat ...
... et al. 1994). User who care about net news will need to rate the news based on certain aspects. Based on the rate from other user, the system can predict what the current user wants. The advance feature of the system including, openness, ease to use, compatibility, scalability and privacy. 2.2 Relat ...
Marketing Recommender Systems: A New Approach in Digital
... incomes and expenditures of population, because purchasing behavior might be something larger than that considered by the company. 3 Related Work Recommender systems have begun an important domain of research during the past years; they compare a user profile to some reference characteristics, and w ...
... incomes and expenditures of population, because purchasing behavior might be something larger than that considered by the company. 3 Related Work Recommender systems have begun an important domain of research during the past years; they compare a user profile to some reference characteristics, and w ...
Collaborative Filtering
... • Tree Augmented naïve Bayes and naïve Bayes optimized by Extended Logic Regression (ELR) – Require extended training periods to produce results beyond simple Bayesian and Pearson correlation ...
... • Tree Augmented naïve Bayes and naïve Bayes optimized by Extended Logic Regression (ELR) – Require extended training periods to produce results beyond simple Bayesian and Pearson correlation ...