Define Semantics

Define Semantics
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Answer :

The semantics of the language defines the truth of each sentence with respect to each possible world. With this semantics, when a particular configuration exists with in an agent, the agent believes the corresponding sentence.
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Last Answer : b) generation and understanding

Which is used to mediate between syntax and semantics? a) Form b) Intermediate form c) Grammer d) All of the mentioned

Description : Which is used to mediate between syntax and semantics? a) Form b) Intermediate form c) Grammer d) All of the mentioned

Last Answer : b) Intermediate form

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Description : What is lexical semantics ?

Last Answer : The branch of morphology that deals with the meaning of words is called lexical semantics .

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Description : What is Semantics ?

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Define Information Extraction.

Description : Define Information Extraction.

Last Answer : It is a process of creating database entries by skimming a text and looking for occurrences of a particular class of object.

Define Information Retrieval (IR).

Description : Define Information Retrieval (IR).

Last Answer :  IR is the task of finding documents that are relevant to user’s need for information. 

Define Segmentation?

Description : Define Segmentation?

Last Answer :  The process of finding the words boundaries in a text with no spaces. 

Define Discourse understanding.

Description : Define Discourse understanding.

Last Answer :  A discourage is any string of language usually one that is more than one sentence long. 

Define Disambiguation.

Description : Define Disambiguation.

Last Answer : The speaker’s aim is to communicate some words in utterance and hearer work is to get back the meaning of the world from the knowledge of situation.

Define Ambiguity.

Description : Define Ambiguity.

Last Answer :  The sentence that does not provide exact meaning are called ambiguous sentence. 

Define Sub categorization.

Description : Define Sub categorization.

Last Answer : E 2 eliminates VP by mentioning which phrases can allow which verbs which are known as sub categorization.

Define DCG.

Description : Define DCG.

Last Answer : The method of rewriting the existing rules in the grammar by the method of augmentation is called as DCG (Define Clause Grammar). 

Define Augmentation.

Description : Define Augmentation.

Last Answer : The process of adding the existing rules of a grammar instead of introducing new rules. It is called Augmentation.

Define Bottom up parsing.

Description : Define Bottom up parsing.

Last Answer :  We start from the leaf nodes (i.e.) with the words and search for a tree with root S. 

Define Top down parsing.

Description : Define Top down parsing. 

Last Answer :  It starts with root node S and search for a tree that has the words as it leaves. 

Define Parsing.

Description : Define Parsing.

Last Answer : Parsing is the process of finding a parse tree for a given input string. It is also known as syntactic analysis.

Define Semantic Interpretation.

Description : Define Semantic Interpretation.

Last Answer :  The process of extracting the meaning of an utterance an expression in some representation language. 

Define Formal Language.

Description : Define Formal Language.

Last Answer :  A formal language is defined as a set of strings of terminal symbols. It is called as words. 

Define Language.

Description : Define Language. 

Last Answer :  Language enables us to communicate most of what we have observed about the environment. 

Define Communication.

Description : Define Communication.

Last Answer : Communication is the international exchange of information brought about by the production and perception of signs drawn from a shared system of conventional signs.

Define Reification.

Description : Define Reification.

Last Answer : The process of treating something abstract and difficult to talk about as though it were concrete and easy to talk about is called as reification. 

Define Similarity nets.

Description : Define Similarity nets.

Last Answer : Similarity net is an approach for arranging models. Similarity net is a representation in which nodes denotes models, links connect similar models and links are tied to different descriptions. 

Define conditional planning.

Description : Define conditional planning.

Last Answer : Conditional planning is a way in which the incompleteness of information is incorporated in terms of adding a conditional step, which involves if – then rules.

Define a consistent plan.

Description : Define a consistent plan.

Last Answer : A consistent plan is one in which there are no contradictions in the ordering or binding constraints. 

Define a complete plan.

Description : Define a complete plan.

Last Answer : A complete plan is one in which every precondition of every step is achieved by some other step. 

Define a solution

Description : Define a solution

Last Answer : A solution is defined as a plan that an agent can execute and that guarantees the achievement of goal. 

Define planning.

Description : Define planning.

Last Answer : Planning can be viewed as a type of problem solving in which the agent uses beliefs about actions and their consequences to search for a solution.

Define TD.

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Last Answer : Temporal Difference learning: The key of TD is to use the observed transitions to adjust the values of the observed states so that they agree with the constraint equations.

Define Active Learning.

Description : Define Active Learning.

Last Answer : The agent must learn what to do. An agent must experience as much as possible of its environment in order to learn how to behave in it.

Define Passive learning.

Description : Define Passive learning.

Last Answer : The agent’s policy is fixed and the task is to learn the utilities of states, this could also involve learning a model of the environment.

Define Neural Networks.

Description : Define Neural Networks.

Last Answer : It consists of nodes or units connected by directed links. A link propagates the activation. Each link has a numeric weight which determines the strength and sign of the connection.

Define EM.

Description : Define EM.

Last Answer : Expectation Maximization: the idea of EM is to pretend that we know the parameters of the model and then to infer the probability that each data point belongs to each component. After that we ... where each component is fitted to the entire data set with each point weighted by the probability. 

Define sum of squared errors.

Description : Define sum of squared errors.

Last Answer : The difference between the actual value yj and the predicated value ( θ1 xj + θ2 ) so E is the sum of squared errors. 

Define Naïve Bayes model.

Description : Define Naïve Bayes model.

Last Answer : In this model, the “class” variable C is the root and the “attribute” variable XI are the leaves. This model assumes that the attributes are conditionally independent of each other, given the class.

Define MDL.

Description : Define MDL.

Last Answer : The MDL (Maximum Description Length), is a learning method which attempts to minimize the size of the hypotheses and data encodings rather than work with probabilities.

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Last Answer : Maximum A Posteriori. A very common approximation is to make predictions based on single most probable hypotheses. This is MAP. 

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Description : Define Bayesian Learning.

Last Answer : It calculates the probability of each hypotheses, given the data and makes predictions on that basis, (i.e.) predictions are made by using all the hypotheses, weighted by their probabilities rather than by using just single “best” hypotheses.

Define constructive induction algorithm.

Description : Define constructive induction algorithm.

Last Answer :  Algorithms that can generate new predicates are called constructive induction algorithms. 

Define Inductive Logic Programming (ILP).

Description : Define Inductive Logic Programming (ILP).

Last Answer : ILP techniques perform KBIL on knowledge that is expressed in first order logic. ILP methods can learn relational knowledge that is not expressible in attribute based systems.

Define knowledge based Inductive learning.

Description : Define knowledge based Inductive learning.

Last Answer : KBIL algorithm finds inductive hypotheses that explain sets of observations with the help of background knowledge.