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This paper investigates the development of a knowledge base (KB) of logical functions, that can be used to do reasoning, from the consolidation of training examples of those logical functions. The work is based on the L2R (Learning to Reason) framework. A L2R agent only needs to answer knowledge queries that are relevant to its environment in a Probably Approximately Correct sense. We develop an L2R...
Building upon the expectation disconfirmation theory and prior satisfaction studies, this study proposes a research model explaining user information satisfaction in knowledge-based virtual communities. The proposed model was tested using an online survey that was conducted among the users of a non-profit-making Bulletin Board Systems established by a local university in mainland China. The results...
Motivated by the increasing importance of knowing which operating systems are running in a given network, we evaluated operating system discovery (OSD) tools. The results indicated a serious lack of accuracy in current OSD tools. This thesis proposes a new approach to OS discovery which addresses the limitations of existing tools and leads to a more flexible, less intrusive, and much more accurate...
Word Sense Disambiguation is one of the essential tasks in the Natural Language Processing that it used to identify the correct sense of words. There are many approaches for Word Sense Disambiguation that in this paper proposes an algorithm based on weighted graph which has few parameters and does not require sense-annotated data for training. Also we used standard data sets to evaluate the algorithm.
Individuals are turning increasingly toward web-based information sources as input for complex decisions. Gathering and evaluating decision criteria in an online context is enticing because of information availability and increased control over the process, but how do these factors impact performance? This study shows how an interaction effect between Social Comparison and Social Facilitation predicts...
Entering-tones are the tones which corresponding Chinese characters are ancient entering-tone characters. The entering tones are recognized using hybrid method which combines rule-based method with statistical method. The syllable which may possibly be an entering-tone or a non-entering tone is called ambiguity syllable. The non-ambiguity syllables can be recognized using rule-based method. The ambiguity...
A common strategy used in rule inductive algorithms is to assign an unseen example, not covered by any rule, to a static default class fixed at the inductive time and not updated thereafter. This paper presents a rule-based system using a Hybrid Possibilistic Inference Mechanism, which combines a Possibilistic Rule-based with a Class-based Reasoning. The inference process gives pre-eminence to Possibilistic...
The Web offers autonomous and frequently useful resources in growing manner. User Generated Content (UGC) like Wikis, Weblogs or Webfeeds often do not have one responsible authorship or declared experts who checked the created content for e.g. accuracy, availability, objectivity or reputation. The user is not able easily, to control the quality of the content he receives. If we want to utilize the...
A lexical ontology is useful as the basic knowledge base in artificial intelligence and computational linguistics application. However, it is insufficient to recognize only existing instances for each concept. Adding new instances into the lexical ontology will expand knowledge in the system. In this paper, we propose an efficient unsupervised instance population system that classifies new instances...
There are many connotative semantic features in Chinese which can help Chinese named entity recognition. Moreover, one of the important strongpoint of maximum entropy model is that it can syncretize features in different granularity and level. With that in mind, many Chinese named entity semantic knowledge bases were established by extracting information from corpus in this paper. However, because...
This paper presents a rule-based approach that utilizes some types of contextual information to improve the accuracy of handwritten mathematical expression(ME) recognition. Mining context from corpus is not practical for ME recognition due to the complexity originated from 2-D nature of MEs. For practicality, we identify typical types of consistencies that are often found in customary usage and general...
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