Reasoning - Question & Answer with solution & Formulas in Hindi & English useful for Download: Download Question & Answer on Reasoning in PDF. 17 फ़रवरी [रीजनिंग] Reasoning Question In Hindi Hello Aspirants, कैसे है आज हम Ratio And Proportion Questions With Answers PDF. Most of the students are finding the reasoning questions and answers in Hindi for preparation of their competitive exams as well as reasoning topics. If they can.
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XEEED coaching reasoning book download in Hindi pdf नोट्स Download करे – प्रिय पाठकों, आज SarkarNaukriHelp आप सब. Reasoning Question In Hindi Show Answer. 2. 'मछली' जैसे जल से सम्बन्धित है, वैसे ही 'चिड़िया' किससे सम्बन्धित है? (A) आकाश; (B). + Reasoning Mixed Questions With Solution Free PDF. GovernmentAdda Free . General Knowledge (Hindi) Questions PDF, Download Now. Geography .
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Direction Questions in Hindi with Answers. Statement: Should Indian scientists working abroad be called back to India?
Yes, They must serve the motherland first and forget about discoveries, honors, facilities and all. No, We have enough talent; let them stay where they want.
So, an argument I is vague. However, talented scientists can be of great benefit to the nation and some alternatives as special incentives or better prospects may be made available to them to retain them within their motherland. So, argument II also does not hold. Statement: Should colleges be given the status of a university in India? No, It is Utopian to think that there will not be nepotism and corruption in awarding degrees by colleges.
Neither I nor II is strong Explanation: Clearly, at the college level, all the students are assessed according to their performance in the University Exams and not on the basis of any criteria of more intimate dealing with the students.
The s and s saw the development of comprehensive theories in computational linguistics , which led to the development of ambitious projects in text comprehension and question answering.
Berkeley in the late s. The system answered questions pertaining to the Unix operating system. It had a comprehensive hand-crafted knowledge base of its domain, and it aimed at phrasing the answer to accommodate various types of users.
Another project was LILOG, a text-understanding system that operated on the domain of tourism information in a German city. The systems developed in the UC and LILOG projects never went past the stage of simple demonstrations, but they helped the development of theories on computational linguistics and reasoning. Recently, specialized natural language QA systems have been developed, such as EAGLi for health and life scientists, and Wolfram Alpha , an online computational knowledge engine that answers factual queries directly by computing the answer from externally sourced curated data.
Architecture[ edit ] As of , QA systems typically included a question classifier module that determines the type of question and the type of answer. It thus makes sense that larger collection sizes generally lend well to better QA performance, unless the question domain is orthogonal to the collection. The notion of data redundancy in massive collections, such as the web, means that nuggets of information are likely to be phrased in many different ways in differing contexts and documents,  leading to two benefits: By having the right information appear in many forms, the burden on the QA system to perform complex NLP techniques to understand the text is lessened.
Correct answers can be filtered from false positives by relying on the correct answer to appear more times in the documents than instances of incorrect ones.
Some question answering systems rely heavily on automated reasoning. Open domain question answering[ edit ] This section does not cite any sources.
January Learn how and when to remove this template message In information retrieval , an open domain question answering system aims at returning an answer in response to the user's question.
The returned answer is in the form of short texts rather than a list of relevant documents . The system uses a combination of techniques from computational linguistics , information retrieval and knowledge representation for finding answers. The system takes a natural language question as an input rather than a set of keywords, for example, "When is the national day of China? Having the input in the form of a natural language question makes the system more user-friendly, but harder to implement, as there are various question types and the system will have to identify the correct one in order to give a sensible answer.
Assigning a question type to the question is a crucial task, the entire answer extraction process relies on finding the correct question type and hence the correct answer type. Keyword extraction is the first step for identifying the input question type .