27036823
A new method in multi-issue negotiation
In this paper we describe a mechanism for automated negotiation in which artificial agents can deal with a multiissue negotiation in a one-to-many way based on some strategies. The negotiation process are governed dynamically by some strategies that emphasize on the diverse processing methods under the considering of different commodity attributes, including dynamic delayed evaluation and response to the received offers, generation of offer group with the same utility. Our analysis shows that the mechanism ensures that bargaining agents could reach a better agreement automatically. We also implement a prototype system to verify the advantages of our mechanism
17411195
Offer Group Generation and Delayed Processing in Multi-Issue Negotiation
In this paper we describe a mechanism for automated negotiation in which artificial agents can deal with a multi-issue negotiation in a one-to-many way based on some strategies. The negotiation process are governed dynamically by some strategies that emphasize on the diverse processing methods under the considering of different commodity attributes, including dynamic delayed evaluation and response to the received offers, generation of offer group with the same utility. Our analysis shows that the mechanism ensures that bargaining agents could reach a better agreement automatically. We also implement a prototype system to verify the advantages of our mechanism.
36918365
C3: A New Learning Scheme to Improve Classification of Rare Category Emails
This paper proposes C3, a new learning scheme to improve classification performance of rare category emails in the early stage of incremental learning. C3 consists of three components: the chief-learner, the co-learners and the combiner. The chief-learner is an ordinary learning model with an incremental learning capability. The chief-learner performs well on categories trained with sufficient samples but badly on rare categories trained with insufficient samples. The co-learners that are focused on the rare categories are used to compensate for the weakness of the chief-learner in classifying new samples of the rare categories. The combiner combines the outputs of both the chief-learner and the co-learner to make a finial classification. The chief-learner is updated incrementally with all the new samples overtime and the co-learners are updated with new samples from rare categories only. After the chief-learner has gained sufficient knowledge about the rare categories, the co-learners become unnecessary and are removed. The experiments on customer emails from an e-commerce company have shown that the C3 model outperformed the Naive Bayes model on classifying the emails of rare categories in the early stage of incremental learning.
23948133
Building Domain Ontology Based on Web Data and Generic Ontology
The automatic or semi-automatic construction of ontology has become a research topic of interest in recent years. This paper describes a mechanism for constructing domain specific ontologies automatically based on web data and generic ontology. Firstly, we employ the hierarchical agglomerative clustering(HAC) algorithm, clustering web pages hierarchically and resulting in a binary tree. Then an algorithm is proposed, which selectd from the binary tree the significative nodes as topics implying concepts of domain interests. Lastly, the Chinese generic ontology, HowNet, is introduced to evolve the topics (together with their hierarchical structures) into domain ontology. We experiment our method in the field of computer hardware based on web pages collected from Chinese BtoC web sites. An in-depth discussion on the experiment results is also given.
5086368
Marker-controlled perception-based mesh segmentation
This paper introduces an interactive marker-controlled mesh segmentation algorithm. In many applications, we need to partition a given mesh according to human perception or particular requirements. The algorithm presented in this paper is based on fast marching watersheds. We refer to the experience of image segmentation area and introduce interactive marker selection. Thus we obviously overcome the difficulty in intuitional segmentation control, and improve the quality of segmentation. The output results show the effectiveness and practicability of the algorithm.
13044783
A New Time-domain Detection Approach with Blind Separation Based on Neural Network
In this paper a new technique is proposed for time-domain detection in energy detection. The proposed scheme is based on a independent-component analysis (ICA): blind separation of unknown source signals. This method not only improves the nicety of time-domain detection for narrow band signal and the sinusoidal signal but also reduces the power of the whole detection system.
11711753
CRM Method for Power Supply Enterprises Based on Analysis of Utility and Customers_ Credit and Multistage Fuzzy Evaluation
As the major customers can choose power supply enterprises independently in electric power marketplace, the enterprises are forced to have to implement CRM, abbreviation for customer relationship management which is an important method of controlling the major customers to prevent their loss. While, in order to making the implementation of CRM more effectively, a problem on how to make a choice of the stimulation method depending on the need of electricity customers needs to be resolved by electricity power supply enterprises. This paper is on the basis of utility theory and multistage fuzzy evaluation, classifying major customers by analyzing and evaluating the level of the customers' credit and the utility of different stimulation methods on different electricity customers, and putting forward the stimulation method for the electricity power supply enterprises to implement CRM. At the end of this paper, this method is confirmed to be reasonable with a simulation example.
5143150
On Miquel's Five-Circle Theorem
Miquel's Five-Circle Theorem is difficult to prove algebraically. In this paper, the details of the first algebraic proof of this theorem is provided. The proof is based on conformal geometric algebra and its accompanying invariant algebra called null bracket algebra, and is the outcome of the powerful computational techniques of null bracket algebra embodying the novel idea breefs.
5525123
FIX: feature-based indexing technique for XML documents
Indexing large XML databases is crucial for efficient evaluation of XML twig queries. In this paper, we propose a feature-based indexing technique, called FIX, based on spectral graph theory. The basic idea is that for each twig pattern in a collection of XML documents, we calculate a vector of features based on its structural properties. These features are used as keys for the patterns and stored in a B+tree. Given an XPath query, its feature vector is first calculated and looked up in the index. Then a further refinement phase is performed to fetch the final results. We experimentally study the indexing technique over both synthetic and real data sets. Our experiments show that FIX provides great pruning power and could gain an order of magnitude performance improvement for many XPath queries over existing evaluation techniques.
29554681
Uniqueness of the generalized Barker sequence of length 6
It is proven that there is a unique generalized Barker sequence of length 6, modulo the group of Barker-preserving transformations. >