We present a new learning algorithm introducing a helpful teacher who models the learners' knowledge. Our algorithm, called learning from extensions (LEX), learns finite-state transducers using only one type of qu...
详细信息
Temporal regularity of pattern appearance can be regarded as an important criterion for measuring the interestingness in several applications like market basket analysis, web administration. gene data analysis, networ...
详细信息
ISBN:
(纸本)9783540889052
Temporal regularity of pattern appearance can be regarded as an important criterion for measuring the interestingness in several applications like market basket analysis, web administration. gene data analysis, network monitoring. and stock market. Even though there have been some efforts to discover periodic patterns in time-series and sequential data, none of the existing works, is appropriate for discovering the patterns that occur regularly in a transactional database. therefore, in this paper, we introduce a novel concept of mining regular patterns from transactional databases and propose an efficient data structure. called Regular Pattern tree (RP-tree in short), that enables a pattern growth-based mining, technique to generate the complete set of regular patterns in a database for regularity threshold. Our comprehensive experimental study shows a user-given that RP-tree is both time and memory efficient in finding regular pattern.
Preference learning has recently received a lot of attention within the machine learning field, concretely learning by pairwise comparisons is a well-established technique in this field. We focus on the problem of lea...
详细信息
ISBN:
(纸本)9783540772255
Preference learning has recently received a lot of attention within the machine learning field, concretely learning by pairwise comparisons is a well-established technique in this field. We focus on the problem of learningthe overall preference weights of a set of alternatives from the (possibly conflicting) uncertain and imprecise information liven by a group of experts into the form of interval pairwise comparison matrices. Because of the complexity of real world problems, incomplete information or knowledge and different patterns of the experts, interval data provide a flexible framework to account uncertainty and imprecision. In this context, we propose a two-stage method in a distance-based framework, where the impact of the data certainty degree is captured. First, it is obtained the group preference matrix that best reflects imprecise information given by the experts. then, the crisp preference weights and the associated ranking of the alternatives are derived from the obtained group matrix. the proposed methodology is made operational by using an Interval Goal Programming formulation.
In telecom industry high installation and marketing costs make it between six to ten times more expensive to acquire a new customer than it is to retain the existing one. Prediction and prevention of customer chum is ...
详细信息
ISBN:
(纸本)3540454853
In telecom industry high installation and marketing costs make it between six to ten times more expensive to acquire a new customer than it is to retain the existing one. Prediction and prevention of customer chum is therefore a key priority for industrial research. While all the motives of customer decision to churn are highly uncertain there is lots of related temporal data sequences generated as a result of customer interaction withthe service provider. Existing churn prediction methods like decision tree typically just classify customers into chumers or non-chumers while completely ignoring the timing of chum event. Given histories of other customers and the current customer's data, the presented model proposes a new k nearest sequence (kNS) algorithm along with temporal sequence fusion technique to predict the whole remaining customer data sequence path up to the chum event. It is experimentally demonstrated that the new model better exploits time-ordered customer data sequences and surpasses the existing churn prediction methods in terms of performance and offered capabilities.
Vis/NIRs technique can be used in non-destructive measurement of the material internal quality in many fields. In this study, a mixed algorithm combined with back-propagation neural networks (BPNNs) and partial least ...
详细信息
the work presented in this paper shows the capability of a connectionist model, based on a statistical technique called Exploratory Projection Pursuit (EPP), to identify anomalous situations related to the traffic whi...
详细信息
Biological research requires information from multiple data sources that use a variety of database-specific formats. Manual gathering of information is time consuming and error-prone, making automateddata aggregation...
详细信息
暂无评论