<prompt> Hlalosa hore na ho sefa ka kopanelo ke eng.nan  <response>: Instruction in English: Explain what is collaborative filtering. . Response in English: Collaborative filtering is a widely used method employed by recommender systems to make suggestions or predictions for an individual based on the behaviors or preferences of other users of the same platform. In other words, it is a technique that uses the collective behavior of a large group of users to help an individual find items they might like or find useful.The underlying assumption of collaborative filtering is that if two individuals show similar interests in certain items, then their preferences for other items are also likely to be similar. This technique can be used to make suggestions for various types of content, including movies, books, music, news articles, and products.There are two main types of collaborative filtering: user-based and item-based. User-based collaborative filtering finds other users with similar tastes or preferences, then recommends items that those users have liked or purchased. Item-based collaborative filtering, on the other hand, uses the behavior of all users to construct relationships between items. If a user has rated or purchased a certain item, the algorithm suggests other items that were commonly rated or purchased along with it.The effectiveness of collaborative filtering depends on the size and quality of the user behavior data that is available. The more information the algorithm has, the better the recommendations it can provide. . Response in Sesotho: Ho sefa ka kopanelo ke mokhoa o sebelisoang haholo o sebelisoang ke litsamaiso tsa khothaletso ho etsa litlhahiso kapa likhakanyo bakeng sa motho ka mong ho latela boitšoaro kapa likhetho tsa basebelisi ba bang ba sethala se le seng. Ka mantsoe a mang, ke mokhoa o sebelisang boitšoaro bo kopanetsoeng ba sehlopha se seholo sa basebelisi ho thusa motho ka mong ho fumana lintho tseo a ka li ratang kapa a ka li fumanang li le molemo. Maikutlo a ka sehloohong a ho sefa ka tšebelisano-moho ke hore haeba batho ba babeli ba bontša thahasello e tšoanang linthong tse itseng, khetho ea bona bakeng sa lintho tse ling le eona e ka na ea tšoana. Mokhoa ona o ka sebelisoa ho etsa litlhahiso bakeng sa mefuta e fapaneng ea litaba, ho kenyelletsa lifilimi, libuka, mino, lingoliloeng tsa litaba le lihlahisoa. Ho na le mefuta e meli ea mantlha ea ho sefa tšebelisano: ho ipapisitsoe le basebelisi le ho ipapisa le lintho. Sesefa se sebelisanang le basebelisi se fumana basebelisi ba bang ba nang le litatso kapa likhetho tse tšoanang, ebe se khothaletsa lintho tseo basebelisi bao ba li ratileng kapa ba li rekileng. Ka lehlakoreng le leng, ho sefa ka kopanelo ho thehiloeng linthong ho sebelisa boitšoaro ba basebelisi bohle ho theha likamano lipakeng tsa lintho. Haeba mosebelisi a fane ka lintlha kapa a rekile ntho e itseng, algorithm e fana ka maikutlo a lintho tse ling tse neng li atisa ho rekoa kapa li rekoa hammoho le eona. Katleho ea ho sefa ka tšebelisano e ipapisitse le boholo le boleng ba data e fumanehang ea boitšoaro ba mosebelisi. Boitsebiso bo bongata boo algorithm e nang le bona, ho ntlafatsa litlhahiso tseo e ka fanang ka tsona. 