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Questions and Answers

What is the approach used by AskMRS to answer queries?

Shallow approach that ignores hard documents and finds easy ones (correct)

Pattern matching to match user questions to a knowledge base

Middle ground approach using large collection of surface matching patterns

Knowledge-rich approach using many NLP techniques

What is the primary intuition behind query rewriting in AskMSR?

The user's question is often pragmatically quite close to sentences that contain the answer

The user's question is often lexically quite close to sentences that contain the answer

The user's question is often semantically quite close to sentences that contain the answer

The user's question is often syntactically quite close to sentences that contain the answer (correct)

How many categories are used to classify questions in AskMSR?

7 (correct)

What is the purpose of step 1 in AskMSR?

To rewrite queries to match sentences that contain the answer Signup and view all the answers

What is the reported percentage of questions that top performing systems can answer?

70% Signup and view all the answers

Which of the following is an example of a knowledge-rich approach?

Harabagiu, Moldovan et al.-SMU/UTD/LCC Signup and view all the answers

What is the primary approach used by AskJeeves?

Pattern matching to match user questions to a knowledge base Signup and view all the answers

What is the purpose of category-specific transformation rules in AskMSR?

To rewrite queries to match sentences that contain the answer Signup and view all the answers

What is the primary focus of semantics and reasoning in QA?

Predicate-argument structure Signup and view all the answers

Which of the following is not a key feature of Natural Language Processing?

Search Engine Optimization Signup and view all the answers

What is the primary goal of inference in QA systems?

To justify an answer through lexical chains Signup and view all the answers

What is the Stanford question answering dataset (SQuAD) used for?

Training neural models for reading comprehension Signup and view all the answers

What is the purpose of mapping question and potential answer LFs in QA systems?

To find the best match between question and answer Signup and view all the answers

What is the primary focus of predicate-argument structure in QA systems?

Detecting sentences with specific objects or close synonyms Signup and view all the answers

What is the benefit of using inference in QA systems?

30% improvement in accuracy Signup and view all the answers

What is the name of the process that involves analyzing sentence syntax and semantics to answer questions?

Syntactic analysis plus semantic Signup and view all the answers

What is the purpose of query rewriting in Web question answering?

To rephrase a query to improve its search engine results Signup and view all the answers

What is the primary function of a Web search engine in the Web question answering process?

To provide top N answers to rephrased queries Signup and view all the answers

What is the purpose of mining N-grams in Web question answering?

To identify relevant keywords and phrases Signup and view all the answers

What is the function of data-type filters in Web question answering?

To boost or lower scores of N-grams based on their matching with regular expressions Signup and view all the answers

What is the limitation of the Web question answering technique described in the content?

It has a limited range of question categories and answer data types Signup and view all the answers

What is the purpose of tiling the answers in Web question answering?

To determine the final answer to a question Signup and view all the answers

What is the primary goal of the Web question answering process?

To determine the final answer to a question Signup and view all the answers

What is the purpose of surface matching patterns in Web question answering?

To match a question with its corresponding answer pattern Signup and view all the answers

Study Notes

Question Answering Systems

Online QA examples include LCC, AnswerBus, EasyAsk, AnswerLogic, and AskJeeves
AskJeeves is a hyped example of QA that uses pattern matching to match user questions to their own knowledge base of questions

Top Performing Systems

Top performing systems can answer around 70% of questions
Approaches include knowledge-rich approaches using many NLP techniques, and shallow approaches like AskMRS

AskMRS: Shallow Approach

AskMRS ignores hard documents and finds easy ones
Steps include:
- Query rewriting: classify question into 7 categories and apply transformation rules
- Sending rewrites to a web search engine and retrieving top N answers
- Mining N-grams: enumerating all N-grams in retrieved phrases and weighting by occurrence count
- Filtering N-grams: using data-type filters to boost scores of matching n-grams
- Tiling the answers: combining scores to get the final answer

Surface Matching Patterns

Surface matching patterns use large collections of surface matching patterns (ISI)
Important features include precision of recognition, coverage of name classes, and mapping into concept hierarchies

Semantics and Reasoning for QA

Semantics and reasoning for QA involve analyzing sentence syntax and semantics
Techniques include predicate-argument structure, syntax to logical forms, and inference

Neural Models for Reading Comprehension

Neural models for reading comprehension use large-scale supervised datasets like the Stanford question answering dataset (SQuAD)

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Description

Find out what vacuum cleaner is recommended by Consumer Guide. Learn about online QA examples and question answering systems.