30668343
Odaies: ontology-driven adaptive Web information extraction system
This paper proposes an ontology-driven self-adapting approach in the semi-structured Web information extraction field, where ontology provides semantic support and plays a central role during the extraction process. It outperforms traditional wrapper systems in adaptiveness and maintenance. Firstly, we build a domain-dependant ontology. Then we design three templates generating algorithms, which have self-adaptiveness and self-maintenance based on the ontology, to perform Web page information extraction. Experiment results show that our prototype system can achieve 100% recall and 97.64% precision.
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.
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.
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.
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.
1111273
A unified approach to a fair document exchange system
This paper aims to propose a solution to unify different approaches to fair document exchange for the development of a flexible, general and secure fair document exchange system capable of guaranteeing strong fairness. The solution caters for a document exchange among any number of parties under various situations. At the heart of this unified solution are methods for a verifiable and recoverable encryption of a symmetric (or conventional) key for document encryption and decryption in a simple and efficient manner. The verifiability means that any party can verify the correctness of a key encrypted without actually viewing the key, and the recoverability implies that the party can be assured that a designated party or a group of designated parties can decrypt the encrypted key to recover the original key. These methods are essential for the unified solution to achieve strong fairness. The main novel contribution of the work presented in this paper is that the proposed unified solution represents the first effort on providing an efficient and unified approach to achieving strong fairness in document exchange under various situations.
16577876
FAME: Adding Multi-Level Authentication to Shibboleth
The paper describes the design of FAME (Flexible Access Middleware Extension) architecture aimed at providing multi-level user authentication service for Shibboleth, which is endorsed by the Joint Information Systems Committee (JISC) as the next generation authentication and authorisation infrastructure for the UK Higher Education community. FAME derives authentication assurance level based upon the strength of the authentication token and protocol used by the user when authenticating and feeds it to the PERMIS authorisation decision engine via Shibboleth to enable more fine-grained access control. In this way, access to resources is controlled according to the strength of the authentication method so that more sensitive resources may require users to identify themselves using a higher level of authentication.
46032361
ERPDB: An Integrated Database of ERP Data for Neuroinformatics Research
Event-related potential (ERP) is the measurement of the brain's electrical activity in response to different types of events, such as attention, words, thinking, or sounds. By measuring the brain's response to such events, we can learn how different types of information are processed. As the mass of recorded ERP data explodes, an automatic and accurate tool to store, manage, and retrieve data readily is of increasing concern in neuroinformatics. In this paper, we describe a relational ERP database that has been constructed using the SQL server 2000 database management system and an IIS web server that has been setup for data retrieval through a custom web interface (http://202.113.232.103:8088/erpdb/index.asp). A novel database structure has been used to store ERP data of different activity channels, which provides a rapid and accurate way for data retrieval within any given range on the time zone with various searching options. The database is divided into: (1) subjects' information and record information and (2) ERP data, which has been structured and standardized in a database table supplemented with unrestricted text files. It can integrate or exchange data with other clinical databases or computer-based information systems through a program based on ADO techniques. Users are able to readily retrieve ERP data through the user-friendly web page interface. All online resources of the database are freely available to the scientific community. As the database develops further, we anticipate it will become a valuable tool that will make a great contribution to everyday clinical practice, teaching, and research work inneuroscience and psychology in the future.
17598350
Certified e-mail delivery with DSA receipts
In this paper we present two variant protocols DSA-CEMD1 and DSA-CEMD2 for certified e-mail delivery with DSA receipts. The protocols are based on a cryptographic primitive called Verifiable and Recoverable Encryption of a Signature (VRES) and are capable of achieving non-repudiation and strong fairness security properties. The novel design of the VRES primitive allows efficiency improvements in comparison with the related certified e-mail delivery protocols based on similar primitives. The protocols employ the services of an off-line and invisible trusted third party (TTP) only in case of dispute. In DSA-CEMD1 the content of the e-mail message is not revealed to the TTP during possible recovery and this is achieved at the cost of some additional cryptographic operations. In DSA-CEMD2 the confidentiality of the message is not protected from the TTP, but the protocol is slightly more efficient.
1453470
Towards an authentication middleware to support ubiquitous Web access
This extended abstract reports our on-going work on the design and development of a flexible multifactor authentication middleware to support secure, finegrained and ubiquitous data access through Web services.