Define Bottom up parsing.

1 Answer

Answer :

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

Related questions

Description : Pick out the correct option about the types of parsing. a) Top-down and bottom-up parsing b) Interpretation and communication c) Roll-up and roll-down d) None of the mentioned

Last Answer : a) Top-down and bottom-up 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. 

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.

Description : How many states are present in parsing? a) 1 b) 2 c) 3 d) 4

Last Answer : c) 3

Description : A network with named nodes and labeled arcs that can be used to represent certain natural language grammars to facilitate parsing. a) Tree Network b) Star Network c) Transition Network d) Complete Network

Last Answer : c) Transition Network

Description : What are the algorithms to have efficient parsing?

Last Answer : i. Left to right parsing algorithm  ii. Chart Parsing algorithm.  iii. Left corner parsing

Description : What are the types of parsing?

Last Answer : i. Top down parsing  ii. Bottom up parsing

Description : Which one from the following is false ? (A) LALR parser is Bottom - Up parser (B) A parsing algorithm which performs a left to right scanning and a right most deviation is RL (1). (C) LR parser is Bottom - Up parser. (D) In LL(1), the 1 indicates that there is a one - symbol look - ahead.

Last Answer : (B) A parsing algorithm which performs a left to right scanning and a right most deviation is RL (1).

Description : Which approach is used for refining a very general rule through ILP? a) Top-down approach b) Bottom-up approach c) Both Top-down & Bottom-up approach d) None of the mentioned

Last Answer : a) Top-down approach

Description : Which object recognition process is an error-prone process? a) Bottom-up segmentation b) Top-down segmentation c) Both Bottom-up & Top-down segmentation d) None of the mentioned

Last Answer : a) Bottom-up segmentation

Description : How to setup Vision Helpdesk Two Way Email Parsing?

Last Answer : I do not, but I went to there website and I see that they have live support which is online right now. If you get frusturated with it I reccomend www.zendesk.com and http://www.jazzdesk.com/

Description : Easy ICS Embedding / Parsing?

Last Answer : I’ve never used it but this looks like it might be useful? http://phpicalendar.net/documentation/index.php/Main_Page

Description : Which of the following derivations does a top-down parser use while parsing an input string ? The input is scanned from left to right. (A) Leftmost derivation (B) Leftmost derivation traced out in reverse (C) Rightmost derivation traced out in reverse (D) Rightmost derivation

Last Answer : (A) Leftmost derivation

Description : The process of assigning load addresses to the various parts of the program and adjusting the code and data in the program to reflect the assigned addresses is called .................. (A) Symbol resolution (B) Parsing (C) Assembly (D) Relocation

Last Answer : (D) Relocation

Description :  The initial state and the legal moves for each side define the __________ for the game. a) Search Tree b) Game Tree c) State Space Search d) Forest

Last Answer : b) Game Tree

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.

Description : Define Information Retrieval (IR).

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

Description : Define Segmentation?

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

Description : Define Discourse understanding.

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

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.

Description : Define Ambiguity.

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

Description : Define Sub categorization.

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

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). 

Description : Define Augmentation.

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

Description : Define Semantic Interpretation.

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

Description : Define Language. 

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

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.

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. 

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. 

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.

Description : Define a consistent plan.

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

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. 

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. 

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.

Description : Define TD.

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.

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.

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.

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.

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. 

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. 

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.

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.

Description : Define MAP.

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

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.

Description : Define constructive induction algorithm.

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

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.

Description : Define knowledge based Inductive learning.

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

Description : Define RBL.

Last Answer : Relevance based Learning; the prior knowledge background concerns the relevance of a set of features to the goal predicate. This knowledge together with the observations, Allows the agent to ... ^ Description |= classifications,  Background ^ Description ^ classifications |= Hypothesis.

Description : Define EBL.

Last Answer : Explanation based learning, from the prior knowledge (or) information; we can infer a general rule. This kind of generalization process called explanation based learning (or) EBL.