Read the following passage carefully and answer the questions given below it. Certain words have been printed in bold to aid in answering some of the questions. In this modern era of big data, the shopping activity is modified a lot because of enormous growth in online shopping websites, also known as E-Tailers. The new age customers prefer to shop through these online portals because of various attractions in countries like India such as easy and cheap availability of the Internet. The primary reason for cheap internet is intense competition between telecoms, for instance, many telecom companies offer free unlimited internet data usage for all of its users in nominal charges. Moreover, searching a suitable E-Commerce website to best suit the customer purchase requirements is not so easy as customers are primarily dependent on conventional search engines like Google, Bing to find a suitable E-Commerce web site. However, when different users search the same ECommerce query, even a most advanced and popular search engine retrieves the same result. Thus, irrespective of the background and personalized tastes of customer submitting the query as most of the **modern** search engines tend to return the results by interpreting the E-Commerce query in various possible ways. Moreover, if the query is **ambiguous** or incomplete, then the situation will get even worse. For instance, for the incomplete E-Commerce search query “Galaxy”, some customers may be interested in links to buy a new Samsung Galaxy series mobile phone, while another customer may be interested in searching links for online booking of tickets for a movie Guardians of the Galaxy Vol. 2. Hence, there is an urgent need for personalized E-Commerce search system. The personalized system may **modify** the ECommerce search query by keeping track of customer's preferences by maintaining his/her profile, search preferences through browsing history, etc. over a period and return results in correct order of ranking with customer’s relevant output links on top to best suit the customer requirements. ECommerce data is explosively increasing on the scale of TeraBytes (TB) to PetaBytes (PB) on a daily basis due to the continuous increase in WWW traffic. This excessive online generated data is commonly known as ‘Big Data’ with emphasis on high values of various popular V's, i.e., Value, Velocity, Variety, Veracity, and Volume.

How do different search engines handle a specific E-commerce query?

Question

Read the following passage carefully and answer the questions given below it. Certain words have been printed in bold to aid in answering some of the questions. In this modern era of big data, the shopping activity is modified a lot because of enormous growth in online shopping websites, also known as E-Tailers. The new age customers prefer to shop through these online portals because of various attractions in countries like India such as easy and cheap availability of the Internet. The primary reason for cheap internet is intense competition between telecoms, for instance, many telecom companies offer free unlimited internet data usage for all of its users in nominal charges. Moreover, searching a suitable E-Commerce website to best suit the customer purchase requirements is not so easy as customers are primarily dependent on conventional search engines like Google, Bing to find a suitable E-Commerce web site. However, when different users search the same ECommerce query, even a most advanced and popular search engine retrieves the same result. Thus, irrespective of the background and personalized tastes of customer submitting the query as most of the **modern** search engines tend to return the results by interpreting the E-Commerce query in various possible ways. Moreover, if the query is **ambiguous** or incomplete, then the situation will get even worse. For instance, for the incomplete E-Commerce search query “Galaxy”, some customers may be interested in links to buy a new Samsung Galaxy series mobile phone, while another customer may be interested in searching links for online booking of tickets for a movie Guardians of the Galaxy Vol. 2. Hence, there is an urgent need for personalized E-Commerce search system. The personalized system may **modify** the ECommerce search query by keeping track of customer's preferences by maintaining his/her profile, search preferences through browsing history, etc. over a period and return results in correct order of ranking with customer’s relevant output links on top to best suit the customer requirements. ECommerce data is explosively increasing on the scale of TeraBytes (TB) to PetaBytes (PB) on a daily basis due to the continuous increase in WWW traffic. This excessive online generated data is commonly known as ‘Big Data’ with emphasis on high values of various popular V's, i.e., Value, Velocity, Variety, Veracity, and Volume.

How do different search engines handle a specific E-commerce query?

Accepted Answer

**Solution:**

1. The passage explains that search engines do not provide personalized or exact product results instantly for every user.

2. Instead, they retrieve and process data from multiple users who search the same query, resulting in similar outputs regardless of individual preferences.

3. This means search engines analyze collective user data to generate results for a particular E-commerce query.

4. Options (a), (c), and (d) do not align with the passage's explanation about how search engines work.

**Answer:** (b) They collect and analyze data from various users to generate results for a given query.

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