<prompt> Hlalosa nyeoe ea tšebeliso ea litsamaiso tsa khothaletsonan  <response>: Instruction in English: Describe a use case for recommender systems . Response in English: Recommender systems are used to help users find the most relevant information, products or services based on their preferences and past behavior. A common use case for recommender systems is on e-commerce websites, where they provide personalized recommendations to users based on their purchase and browsing history, as well as the behavior of similar users.For example, Amazon uses a recommender system on its website to suggest products that a user might be interested in purchasing. When a user visits the website, the algorithm analyzes their purchase history and items they have viewed to show them relevant products. It also takes into account the behavior of other users with similar interests and shows recommendations based on what those users have viewed or purchased. This helps to improve the shopping experience for the user and increases the likelihood of a purchase, thus driving sales for the e-commerce platform.Recommender systems can also be used in a variety of other scenarios, such as suggesting movies or TV shows on a streaming platform, recommending news articles or blog posts, or even suggesting friends or connections on a social media platform. In all of these cases, the goal is to provide users with personalized, relevant content or connections that enhance their experience on the platform. . Response in Sesotho: Litsamaiso tsa likhothaletso li sebelisoa ho thusa basebelisi ho fumana tlhaiso-leseling e nepahetseng, lihlahisoa kapa litsebeletso ho latela seo ba se ratang le boitšoaro ba bona ba nakong e fetileng. Nyeoe e tloaelehileng ea tsebeliso ea litsamaiso tsa khothaletso ke liwebsaeteng tsa e-commerce, moo ba fanang ka likhothaletso tsa motho ka mong ho basebelisi ho latela nalane ea bona ea ho reka le ho bala, hammoho le boitšoaro ba basebelisi ba tšoanang. Mohlala, Amazon e sebelisa sistimi ea khothaletso ho webosaete ea eona ho fana ka tlhahiso ea lihlahisoa tseo mosebelisi a ka ratang ho li reka. Ha mosebelisi a etela sebaka sa marang-rang, algorithm e sekaseka nalane ea theko ea bona le lintho tseo ba li boneng ho ba bontša lihlahisoa tse amehang. E boetse e nahanela boitšoaro ba basebelisi ba bang ba nang le lithahasello tse tšoanang me e bontša likhothaletso tse thehiloeng ho seo basebelisi bao ba se boneng kapa ba se rekileng. Sena se thusa ho ntlafatsa boiphihlelo ba ho reka bakeng sa mosebelisi le ho eketsa menyetla ea ho reka, ka hona ho tsamaisa thekiso bakeng sa sethala sa e-commerce. Sistimi ea likhothaletso e ka sebelisoa maemong a mang a fapaneng, joalo ka ho fana ka maikutlo a lifilimi kapa mananeo a seea-le-moea-pono sethaleng sa ho phallela, ho buella lingoloa tsa litaba kapa li-blog, kapa ho fana ka maikutlo a metsoalle kapa likhokahano sethaleng sa litaba tsa sechaba. Maemong ana kaofela, sepheo ke ho fa basebelisi litaba tse ikhethileng, tse amehang kapa likhokahano tse ntlafatsang boiphihlelo ba bona sethaleng. 