<prompt> Bapisa le ho bapisa li-algorithms tse peli tse fapaneng tsa enjine ea patlo.nan  <response>: Instruction in English: Compare and contrast two different search engine algorithms. . Response in English: A search engine algorithm is a set of rules that dictate how a search engine like Google or Bing ranks web pages to present results relevant to the query typed by a user. Two of the most commonly used search engine algorithms are Googles PageRank and Bings RankNet. PageRank algorithm: Developed by Google, PageRank is an algorithm that measures the importance of web pages based on the quality and quantity of links pointing to them. The algorithm works on the principle that relevant and important web pages are likely to receive a higher number of links from other websites. So, the more high-quality external links pointing to a page, the higher its PageRank score. PageRank also takes into consideration the linking pages own relevance and quality before assigning a score. The pages with the highest PageRank score are the ones that show up at the top of the Google search results.RankNet algorithm: Bings RankNet is a machine-learning-based algorithm that processes user queries and ranks web pages according to their relevance to the query. It is a type of neural network algorithm that starts with a large number of features, such as the keyword in the web page title, the location and frequency of keywords in the page, and the proximity of keywords in search queries to determine which pages are most relevant to the user. The algorithm constantly updates itself based on user feedback such as clicks on the displayed search results, making the results more relevant over time.In summary, PageRank ranks web pages based on their link popularity, while RankNet relies on machine learning and user feedback to provide highly relevant search results. While both algorithms process keyword information, PageRanks primary focus is on external links, while RankNets involves using a range of other features to determine relevance. . Response in Sesotho: Algorithm ea enjine ea ho batla ke sete ea melao e laolang hore na enjine ea ho batla joalo ka Google kapa Bing e beha maemo joang maqepheng a webo ho hlahisa liphetho tse amanang le potso e tlatsitsoeng ke mosebelisi. Li-algorithms tse peli tsa enjine ea ho batla tse sebelisoang haholo ke Googles PageRank le Bings RankNet. PageRank algorithm: E ntlafalitsoe ke Google, PageRank ke algorithm e lekanyang bohlokoa ba maqephe a marang-rang ho latela boleng le bongata ba likhokahano tse li supang. Algorithm e sebetsa ka molao-motheo oa hore maqephe a marang-rang a bohlokoa le a bohlokoa a ka fumana palo e phahameng ea likhokahano ho tsoa liwebsaeteng tse ling. Kahoo, lihokelo tsa kantle tsa boleng bo holimo tse supang leqephe, lintlha tsa lona tsa PageRank li phahame. PageRank e boetse e ela hloko bohlokoa ba leqephe le hokahanyang le boleng ba eona pele e fana ka lintlha. Maqephe a nang le lintlha tse phahameng ka ho fetisisa tsa PageRank ke a hlahang ka holimo ho liphetho tsa lipatlisiso tsa Google. RankNet algorithm: Bings RankNet ke algorithm ea ho ithuta ka mochini e sebetsanang le lipotso tsa basebelisi le ho beha maemo a maqephe a tepo ho latela kamano ea ona le potso. Ke mofuta oa neural network algorithm e qalang ka palo e kholo ea likarolo, joalo ka lebitso la sehlooho sehloohong sa leqephe la webo, sebaka le makhetlo a mangata a mantsoe a sehlooho leqepheng, le ho ba haufi ha mantsoe a bohlokoa lipotsong tsa lipatlisiso ho fumana hore na ke maqephe afe. e bohlokoa haholo ho mosebelisi. Algorithm e lula e inchafatsa e ipapisitse le maikutlo a basebelisi joalo ka ho tobetsa liphetho tse bontsitsoeng, e leng se etsang hore liphetho li be tsa bohlokoa ha nako e ntse e ea. Ka bokhutsoanyane, PageRank e beha maemo a maqephe a tepo ho ipapisitse le botumo ba lihokelo tsa bona, athe RankNet e itsetleha ho thuto ea mochini le maikutlo a basebelisi ho fana ka liphetho tsa lipatlisiso tse bohlokoa haholo. Le ha li-algorithms ka bobeli li sebetsana le tlhaiso-leseling ea mantsoe a sehlooho, sepheo sa mantlha sa PageRank ke lihokelo tsa kantle, athe RankNet e kenyelletsa ho sebelisa mefuta e meng ea likarolo ho bona bohlokoa. 