A NATURAL REPRESENTATION OF BOUNDED LATTICES There
... As a consequence we obtain our representation theorem. Theorem 1.7. Any bounded lattice L is isomorphic to the set of all MPM’s D(L) −→ e 2 ordered by the rule ϕ ≤ ψ iff ϕ−1 (1) ⊆ ψ −1 (1). Our way of reconstructing a lattice from its dual space is similar to the methods used in the formal concept a ...
... As a consequence we obtain our representation theorem. Theorem 1.7. Any bounded lattice L is isomorphic to the set of all MPM’s D(L) −→ e 2 ordered by the rule ϕ ≤ ψ iff ϕ−1 (1) ⊆ ψ −1 (1). Our way of reconstructing a lattice from its dual space is similar to the methods used in the formal concept a ...
IOSR Journal of Research & Method in Education (IOSR-JRME)
... most of the mental process. The self is one’s inner world. In the development of human personality, behavior and social interactions, Self Concept plays a vital role. Self Concept is the internal compass which directs a person’s physical and metaphysical outlook, beliefs and attitudes and human rela ...
... most of the mental process. The self is one’s inner world. In the development of human personality, behavior and social interactions, Self Concept plays a vital role. Self Concept is the internal compass which directs a person’s physical and metaphysical outlook, beliefs and attitudes and human rela ...
Artificial Intelligence and the SAS® System: Why You Have to Teach the SAS® System about SEX!
... To understand a question or query, SAS/ENGLISH software uses an information storage facility, or data model, called the Knowledge Base (KB). The KB describes the data in terms of real-world concepts, relationships, and vocabulary. This type of information is cal· led domain·s'pecific information. It ...
... To understand a question or query, SAS/ENGLISH software uses an information storage facility, or data model, called the Knowledge Base (KB). The KB describes the data in terms of real-world concepts, relationships, and vocabulary. This type of information is cal· led domain·s'pecific information. It ...
Classifier Conditional Posterior Probabilities
... the k-nearest neighbour rule (k-NN). Many others just produce linear discriminant functions, or are, like the 1-NN rule, based on very local information that can’t be used for density estimation. Neural network classifiers usually have [0,1] outputs that, if well trained, after normalization may be ...
... the k-nearest neighbour rule (k-NN). Many others just produce linear discriminant functions, or are, like the 1-NN rule, based on very local information that can’t be used for density estimation. Neural network classifiers usually have [0,1] outputs that, if well trained, after normalization may be ...
Dowling, T.A.; (1972)A class of geometric lattices based on finite groups."
... Theorem 6 and the specializations of Theorems 1-5, 7 and 10 to that case appear in [5]; Theorems 8, 9, and 11 have no counterpart there. Although most of the extensions of the results in [5] to an arbitrary finite group are straightforward, we include them here not only to make the present paper sel ...
... Theorem 6 and the specializations of Theorems 1-5, 7 and 10 to that case appear in [5]; Theorems 8, 9, and 11 have no counterpart there. Although most of the extensions of the results in [5] to an arbitrary finite group are straightforward, we include them here not only to make the present paper sel ...
Ontology learning from text based on multi
... such as ontology languages and terminology. Then we present the state-of-the-art in automatic ontology learning focusing on the main approaches associated with the main subtasks of ontology language development (i.e., taxonomy generation and mining of non-taxonomic relations) along with tools from t ...
... such as ontology languages and terminology. Then we present the state-of-the-art in automatic ontology learning focusing on the main approaches associated with the main subtasks of ontology language development (i.e., taxonomy generation and mining of non-taxonomic relations) along with tools from t ...
Semantic Outlier Detection for Affective Common-Sense Reasoning and Concept-Level Sentiment Analysis Erik Cambria
... negative affective valence. Thus, by exploiting the information sharing property of TSVD, concepts with the same affective valence are likely to have similar features – that is, concepts conveying the same emotion tend to fall near each other in AffectiveSpace. Concept similarity does not depend on ...
... negative affective valence. Thus, by exploiting the information sharing property of TSVD, concepts with the same affective valence are likely to have similar features – that is, concepts conveying the same emotion tend to fall near each other in AffectiveSpace. Concept similarity does not depend on ...
Conceptual combination - City, University of London
... work as a complete account, since an exemplar only becomes relevant to a situation when it is analysed. One can only categorize novel instances on the basis of their similarity to remembered exemplars if there is some means of determining similarity of the relevant kind. But this determination of si ...
... work as a complete account, since an exemplar only becomes relevant to a situation when it is analysed. One can only categorize novel instances on the basis of their similarity to remembered exemplars if there is some means of determining similarity of the relevant kind. But this determination of si ...
Ontology construction for information classification
... ontology as well as giving the summary and results. This type of method is different from the above-mentioned three methods since, the rules in the knowledge base can be regarded as a kind of ontological manifestation. The rules in the knowledge base are used to assemble related ontology (Alani et a ...
... ontology as well as giving the summary and results. This type of method is different from the above-mentioned three methods since, the rules in the knowledge base can be regarded as a kind of ontological manifestation. The rules in the knowledge base are used to assemble related ontology (Alani et a ...
Full text
... of moving in the “down” direction. These were the objects of study by Lauren Williams [3]. Using Zeilberger’s generating function approach, she derived simple closed forms for counting n-step “up-side self-avoiding walks” (which we denote by n-ussaws) on various lattices. In this section, we derive ...
... of moving in the “down” direction. These were the objects of study by Lauren Williams [3]. Using Zeilberger’s generating function approach, she derived simple closed forms for counting n-step “up-side self-avoiding walks” (which we denote by n-ussaws) on various lattices. In this section, we derive ...
Object Focused Q-learning for Autonomous Agents
... also needs either an initial policy that performs well or a good cost heuristic of the domain. Our approach does not have any of these requirements and relies solely on on-line exploration of the domain. In OF-Q, each object produces its own reward signal and the algorithm learns an independent Q-fu ...
... also needs either an initial policy that performs well or a good cost heuristic of the domain. Our approach does not have any of these requirements and relies solely on on-line exploration of the domain. In OF-Q, each object produces its own reward signal and the algorithm learns an independent Q-fu ...
Generating Concept Map Exercises from Textbooks
... Over a few hours, we manually clustered 4371 biology triples available on the Internet1 that span the two topics of molecules & cells and population biology. Although these two topics represent a small subset of biology topics, we hypothesize that as the extremes of levels of description in biology, ...
... Over a few hours, we manually clustered 4371 biology triples available on the Internet1 that span the two topics of molecules & cells and population biology. Although these two topics represent a small subset of biology topics, we hypothesize that as the extremes of levels of description in biology, ...
Knowledge Acquisition Via Incremental Conceptual Clustering
... than restricting search to be unidirectional, both generalization and specialization operators are supplied. Bidirectional mobility allows an incremental system to recover from a bad learning path. In learning from examples, Winston's (1975) 'ARCH' program fits this view of incremental processing; i ...
... than restricting search to be unidirectional, both generalization and specialization operators are supplied. Bidirectional mobility allows an incremental system to recover from a bad learning path. In learning from examples, Winston's (1975) 'ARCH' program fits this view of incremental processing; i ...
An Efficient Hardware Implementation for AI applications
... on AGs. We have improved previous approaches by reducing the number of required processing elements by a factor of n (length of input string). This fact allowed us to use only one component i.e. a single FPGA board, eliminating the need for an external microprocessor, as presented in previous works ...
... on AGs. We have improved previous approaches by reducing the number of required processing elements by a factor of n (length of input string). This fact allowed us to use only one component i.e. a single FPGA board, eliminating the need for an external microprocessor, as presented in previous works ...
Reasoning with Axioms: Theory and Practice
... objects they describe to be reasoned with. Of particular interest is the computation of implied subsumption relationships between concepts, based on the assertions in the terminology, and the maintenance of a concept hierarchy (partial ordering) based on the subsumption relationship [WS92]. The prob ...
... objects they describe to be reasoned with. Of particular interest is the computation of implied subsumption relationships between concepts, based on the assertions in the terminology, and the maintenance of a concept hierarchy (partial ordering) based on the subsumption relationship [WS92]. The prob ...
A Closest Fit Approach to Missing Attribute Values in Preterm Birth
... given case with a missing attribute value, we may look for the closest fitting cases within the same concept, as defined by the case with missing attribute value, or in all concepts, i.e., among all cases. The former algorithm is called concept closest fit, the latter is called global closest fit. S ...
... given case with a missing attribute value, we may look for the closest fitting cases within the same concept, as defined by the case with missing attribute value, or in all concepts, i.e., among all cases. The former algorithm is called concept closest fit, the latter is called global closest fit. S ...
The Square of Opposition in Orthomodular Logic - Philsci
... 1) Propositions about the properties of the physical system are interpreted in the orthomodular lattice of closed subspaces of H. Thus, we retain this structure in our extension. 2) Given a proposition about the system, it is possible to define a context from which one can predicate with certainty a ...
... 1) Propositions about the properties of the physical system are interpreted in the orthomodular lattice of closed subspaces of H. Thus, we retain this structure in our extension. 2) Given a proposition about the system, it is possible to define a context from which one can predicate with certainty a ...
An Efficient Approach to the Clustering of Large Data Sets Using P
... It is important to observe that the criterion for correlation is a function of the attribute values. If attributes are correlated over all but not for the value of a particular test sample no join is performed. One may, e.g., expect that in a classification problem of student satisfaction with a co ...
... It is important to observe that the criterion for correlation is a function of the attribute values. If attributes are correlated over all but not for the value of a particular test sample no join is performed. One may, e.g., expect that in a classification problem of student satisfaction with a co ...
9.4 Why do we want machine learning
... is that machines cannot be called Intelligent until they are able to learn to do new things and adapt to new situations, rather than simply doing as they are told to do. There can be little question that the ability to adapt to new surroundings and to solve new problems is an important characteristi ...
... is that machines cannot be called Intelligent until they are able to learn to do new things and adapt to new situations, rather than simply doing as they are told to do. There can be little question that the ability to adapt to new surroundings and to solve new problems is an important characteristi ...
PDF
... Stains, Dirtiness, Bumps and Other_Faults. The goal was to train machine learning for automatic pattern recognition. The dataset includes 1941 instances, which have been labeled by different fault types. Table 1 shows class distribution and list of attributes. The detailed information and the whole ...
... Stains, Dirtiness, Bumps and Other_Faults. The goal was to train machine learning for automatic pattern recognition. The dataset includes 1941 instances, which have been labeled by different fault types. Table 1 shows class distribution and list of attributes. The detailed information and the whole ...
slides
... quasiequations from the previous slide Moreover it is decidable if such a proof can be found Use this result to show that x (y ...
... quasiequations from the previous slide Moreover it is decidable if such a proof can be found Use this result to show that x (y ...
a novel approach to construct decision tree using quick c4
... ID3 picks predictors and their splitting values based on the gain in information that the split or splits provide. Gain represents the difference between the amount of information that is needed to correctly make a prediction before a split is made and after the split has been made. If the amount of ...
... ID3 picks predictors and their splitting values based on the gain in information that the split or splits provide. Gain represents the difference between the amount of information that is needed to correctly make a prediction before a split is made and after the split has been made. If the amount of ...
Category Theory Example Sheet 1
... 5. Let L be a distributive lattice (i.e. a partially ordered set with finite joins (suprema, ∨) and meets (infima, ∧), satisfying the distributive law a ∧ (b ∨ c) = (a ∧ b) ∨ (a ∧ c) for all a, b, c ∈ L). Show that there is a category MatL whose objects are the natural numbers, and whose morphisms ...
... 5. Let L be a distributive lattice (i.e. a partially ordered set with finite joins (suprema, ∨) and meets (infima, ∧), satisfying the distributive law a ∧ (b ∨ c) = (a ∧ b) ∨ (a ∧ c) for all a, b, c ∈ L). Show that there is a category MatL whose objects are the natural numbers, and whose morphisms ...
View PDF - Oriental Journal of Computer Science and Technology
... With the rapid growth in size and number of available databases in commercial, industrial, administrative and other applications, it is necessary and interesting to examine how to extract knowledge from huge amount of data. There are several mining algorithms available to solve diverse data mining p ...
... With the rapid growth in size and number of available databases in commercial, industrial, administrative and other applications, it is necessary and interesting to examine how to extract knowledge from huge amount of data. There are several mining algorithms available to solve diverse data mining p ...