{"id":16440,"date":"2022-06-23T02:00:48","date_gmt":"2022-06-23T02:00:48","guid":{"rendered":"https:\/\/blog.datumo.com\/en\/?p=16440"},"modified":"2024-10-22T09:02:18","modified_gmt":"2024-10-22T09:02:18","slug":"easiest-way-to-create-a-simple-recommendation-service","status":"publish","type":"post","link":"https:\/\/blog.datumo.com\/en\/tech\/16440","title":{"rendered":"Easiest Way to Create a Simple Recommendation Service"},"content":{"rendered":"<meta http-equiv=\"refresh\" content=\"0; url=https:\/\/datumo.com\/en\/easiest-way-to-create-a-simple-recommendation-service\/\">\r\n\r\n<p>[vc_row pix_particles_check=&#8221;&#8221;][vc_column]<div id=\"el1646799961152-e3ee06c0-4e82\" class=\"w-100 d-block \"><\/div><div class=\"pix-content-box card      vc_custom_1654577545529 custom-responsive-75538105   rounded-lg bg- w-100  \"   ><div class=\"\" style=\"z-index:30;position:relative;\">[vc_column_text]<\/p>\r\n<p style=\"text-align: left;\"><span style=\"font-size: 14pt;\"><strong>\ud83d\udd11<\/strong> <strong>In 9 minutes you will learn:<br \/>\r\n<\/strong><\/span><\/p>\r\n<p>&nbsp;<\/p>\r\n<ul>\r\n<li>The idea of recommendation system<\/li>\r\n<li>Techniques used in recommendation systems<\/li>\r\n<li>4 Phases of building your own recommendation system<\/li>\r\n<\/ul>\r\n<p>[\/vc_column_text]<\/div><\/div>[\/vc_column][\/vc_row][vc_row pix_particles_check=&#8221;&#8221;][vc_column]<div id=\"el1650294698986-a1b962b5-ef42\" class=\"w-100 d-block \"><\/div>[vc_column_text css=&#8221;.vc_custom_1655949926688{padding-top: 40px !important;padding-right: 20px !important;padding-bottom: 40px !important;padding-left: 20px !important;}&#8221;]<\/p>\r\n<p id=\"dd5a\" class=\"pw-post-body-paragraph xt xu wo bn b xv xw hk xx xy xz ho ya yb yc yd ye yf yg yh yi yj yk yl ym yn jn iz\" style=\"text-align: left;\" data-selectable-paragraph=\"\">We will talk about how to create a recommendation system with very little difficulty, but before that, we will talk about the different Machine Learning-based techniques used in implementing these systems. There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.<\/p>\r\n<p style=\"text-align: left;\" data-selectable-paragraph=\"\">A basic example of a recommendation system from real life can be online shopping through Amazon or other e-commerce. When you purchase something, let\u2019s say a phone, you will get a recommendation to buy a headphone or a screen protector to go with your phone. Another example can be Netflix\u2019s recommendation engine. If you watch a particular genre of movies on Netflix e.g. action movies, you will soon see the recommendations of the same or a genre similar to the movie that you previously watched. The reason Netflix is able to understand viewers\u2019 preferences so well and is also able to predict the next movie or show that the viewers would like to watch is achieved through the magic of a recommendation engine. By the end of this tutorial, you will not only be able to create a recommendation system on your own, but you will also be able to understand the techniques and the logic behind these systems. So without further ado, let\u2019s get started!<\/p>\r\n<figure id=\"attachment_16442\" aria-describedby=\"caption-attachment-16442\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img fetchpriority=\"high\" decoding=\"async\" class=\"wp-image-16442 size-full\" src=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/1_d1L3PQOzyy9TCGzgzexmgw.png\" alt=\"\" width=\"700\" height=\"376\" srcset=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/1_d1L3PQOzyy9TCGzgzexmgw.png 700w, https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/1_d1L3PQOzyy9TCGzgzexmgw-300x161.png 300w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><figcaption id=\"caption-attachment-16442\" class=\"wp-caption-text\">Today, recommendations are prevalent all over our daily lives.<\/figcaption><\/figure>\r\n<p data-selectable-paragraph=\"\">[\/vc_column_text][\/vc_column][\/vc_row][vc_section full_width=&#8221;stretch_row&#8221; pix_over_visibility=&#8221;&#8221; css=&#8221;.vc_custom_1650444445523{padding-top: 80px !important;padding-bottom: 80px !important;background-color: #f8f9fa !important;}&#8221; el_id=&#8221;pix_section_program&#8221;][vc_row full_width=&#8221;stretch_row&#8221; pix_particles_check=&#8221;&#8221;][vc_column content_align=&#8221;text-center&#8221; offset=&#8221;vc_col-lg-offset-0 vc_col-lg-12 vc_col-md-offset-1 vc_col-md-10&#8243;]<div id=\"el1650442503491-f5da6b2f-fa35\" class=\"mb-3 text-left \"><h2 class=\"mb-32 pix-sliding-headline font-weight-bold secondary-font\" data-class=\"secondary-font text-heading-default\" data-style=\"\">What is a Recommendation System?<\/h2><\/div>[vc_column_text css=&#8221;.vc_custom_1655950003790{padding-top: 40px !important;}&#8221;]<\/p>\r\n<p style=\"text-align: left;\">To explain what a recommendation system truly is, we will make an analogy between the behaviors of human beings and those of these recommendation systems. Imagine a friend who is familiar with your taste in movies and always recommends movies that you end up watching again and again. Recommendation systems work very much in the same manner. They are like your friends, who know your tastes, likes, and dislikes and make recommendations of things to you accordingly. The question is, how do these recommendation systems know so much about you? Well, recommendation systems\u00a0<em class=\"sf\">basically filter data by using different algorithms and then recommend the most relevant items to you<\/em>. They first understand the past behavior of a user, based on his\/her activity, and on the basis of that, they recommend products that the user is likely to buy or use. The next item that you buy on Amazon, the next show that you watch on Netflix, the next video that you watch on YouTube, the next friend that you add on Facebook, and the next song that you listen to on Spotify, all work on the same principles of recommendation systems.<\/p>\r\n<p>&nbsp;<\/p>\r\n<figure id=\"attachment_16443\" aria-describedby=\"caption-attachment-16443\" style=\"width: 700px\" class=\"wp-caption aligncenter\"><img decoding=\"async\" class=\"wp-image-16443 size-full\" src=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/0_DaW6jCmPmXKT4Ikf.png\" alt=\"\" width=\"700\" height=\"436\" srcset=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/0_DaW6jCmPmXKT4Ikf.png 700w, https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/0_DaW6jCmPmXKT4Ikf-300x187.png 300w\" sizes=\"(max-width: 700px) 100vw, 700px\" \/><figcaption id=\"caption-attachment-16443\" class=\"wp-caption-text\">Netflix might know so much more than you can imagine.<\/figcaption><\/figure>\r\n<p data-selectable-paragraph=\"\">[\/vc_column_text][\/vc_column][\/vc_row][\/vc_section][vc_row pix_particles_check=&#8221;&#8221;][vc_column]<div id=\"el1650442607008-a85a832d-43f0\" class=\"w-100 d-block \"><\/div><div  class=\"pix-heading-el text-left \"><div><div class=\"slide-in-container\"><h2 class=\"text-heading-default font-weight-bold heading-text el-title_custom_color mb-12\" style=\"\" data-anim-type=\"\" data-anim-delay=\"0\">Techniques used in Recommendation Systems<\/h2><\/div><\/div><\/div>[vc_column_text css=&#8221;.vc_custom_1655952222919{padding-top: 40px !important;}&#8221;]<\/p>\r\n<p id=\"e6e2\" class=\"pw-post-body-paragraph xt xu wo bn b xv xw hk xx xy xz ho ya yb yc yd ye yf yg yh yi yj yk yl ym yn jn iz\" data-selectable-paragraph=\"\">The most common types of recommendation systems are\u00a0<em class=\"sf\">Content-Based\u00a0<\/em>and\u00a0<em class=\"sf\">Collaborative Based\u00a0<\/em>Filtering recommendation systems.<\/p>\r\n<figure class=\"yp yq yr ys vj yt jc jd paragraph-image\"><\/figure>\r\n<p>&nbsp;<\/p>\r\n<p><img decoding=\"async\" class=\"aligncenter size-full wp-image-16444\" src=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/1_KZl97_Qtk4ozsV1ULSFYcg.png\" alt=\"\" width=\"556\" height=\"516\" srcset=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/1_KZl97_Qtk4ozsV1ULSFYcg.png 556w, https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/1_KZl97_Qtk4ozsV1ULSFYcg-300x278.png 300w\" sizes=\"(max-width: 556px) 100vw, 556px\" \/><\/p>\r\n<p>&nbsp;<\/p>\r\n<h5><strong class=\"bn ml\">Content-Based Filtering<\/strong><\/h5>\r\n<p>&nbsp;<\/p>\r\n<p id=\"3d9a\" class=\"pw-post-body-paragraph xt xu wo bn b xv yz hk xx xy za ho ya yb zb yd ye yf zc yh yi yj zd yl ym yn jn iz\" data-selectable-paragraph=\"\">In Content-Based Filtering, items are recommended to users on the basis of being similar to what the user likes, and that is known by the user\u2019s previous actions or explicit feedback given by him\/her. We will try to understand this technique through an example. Let\u2019s say that we have a user by the name of user X. User X has watched a movie M1 which belonged to the genre of action. She gave this movie a rating of 5 (out of 5). She watched another movie M2, which belonged to the genre of action as well, and gave it a rating of 4. From this, we can understand that user X enjoys watching action movies and we came to this conclusion because of the high ratings that she has given to these movies. Let\u2019s say the third movie, M3 has recently been released and is of the same genre i.e. action. It also has some similarities with the previous movies e.g. the lead actor, director, etc. Now, the recommendation system will suggest this movie to user X on the basis of User 1\u2019s profile.<\/p>\r\n<blockquote>\r\n<p data-selectable-paragraph=\"\">Main idea: Recommend items to customer X which are similar to previous items rated highly by X.<\/p>\r\n<\/blockquote>\r\n<p id=\"9d7d\" class=\"pw-post-body-paragraph xt xu wo bn b xv yz hk xx xy za ho ya yb zb yd ye yf zc yh yi yj zd yl ym yn jn iz\" data-selectable-paragraph=\"\">For each item, i.e. a movie, website, blog, etc., an item profile is created and this profile becomes a set of feature vectors. For a movie, such feature vectors would consist of the writer, actor, director, etc. Important features are extracted from these item profiles and are used to build the User Profile which is the weighted average of rated item profiles.<\/p>\r\n<p>&nbsp;<\/p>\r\n<h5><\/h5>\r\n<h5><\/h5>\r\n<h5><strong class=\"bn ml\">Collaborative Based Filtering<\/strong><\/h5>\r\n<p>&nbsp;<\/p>\r\n<p id=\"2934\" class=\"pw-post-body-paragraph xt xu wo bn b xv yz hk xx xy za ho ya yb zb yd ye yf zc yh yi yj zd yl ym yn jn iz\" data-selectable-paragraph=\"\">Collaborative Based Filtering utilizes the quality judgments of others who are similar to the target user. Consider an example where we have 2 users, X and Y. X watches a movie M1 and gives it a rating of 5. User Y watches the same movie and gives it a rating of 4. User X watches movie M2 which is coincidentally also seen by user Y and both give it a rating of 4. User X watches a third movie M3 and gives it a rating of 5. Now, since the ratings of the two movies, M1 and M2, given by X and Y are so similar to each other, it is highly likely that the movie M3 (rated as 5 by user X) will also be liked by the user Y. The recommendation system will therefore recommend the movie M3 for user Y to watch.<\/p>\r\n<blockquote>\r\n<p class=\"pw-post-body-paragraph xt xu wo bn b xv yz hk xx xy za ho ya yb zb yd ye yf zc yh yi yj zd yl ym yn jn iz\" data-selectable-paragraph=\"\">Main idea: Consider user X and find a set N of other users whose ratings are similar to X\u2019s ratings. Then, estimate X\u2019s ratings based on ratings of users in N.<\/p>\r\n<\/blockquote>\r\n<p>&nbsp;<\/p>\r\n<p data-selectable-paragraph=\"\"><img loading=\"lazy\" decoding=\"async\" class=\"aligncenter wp-image-16446\" src=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/Frame-2755.png\" alt=\"\" width=\"800\" height=\"571\" srcset=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/Frame-2755.png 1002w, https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/Frame-2755-300x214.png 300w, https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/Frame-2755-768x548.png 768w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><\/p>\r\n<p>[\/vc_column_text]<div id=\"el1650442651668-7359ff25-270a\" class=\"w-100 d-block \"><\/div><div id=\"el1650294913061-211813f5-5f2d\" class=\"w-100 d-block \"><\/div>[\/vc_column][\/vc_row][vc_section full_width=&#8221;stretch_row&#8221; pix_over_visibility=&#8221;&#8221; css=&#8221;.vc_custom_1650444445523{padding-top: 80px !important;padding-bottom: 80px !important;background-color: #f8f9fa !important;}&#8221;][vc_row full_width=&#8221;stretch_row&#8221; pix_particles_check=&#8221;&#8221;][vc_column content_align=&#8221;text-center&#8221; offset=&#8221;vc_col-lg-offset-0 vc_col-lg-12 vc_col-md-offset-1 vc_col-md-10&#8243;]<div  class=\"pix-heading-el text-left \"><div><div class=\"slide-in-container\"><h2 class=\"text-heading-default font-weight-bold heading-text el-title_custom_color mb-12\" style=\"\" data-anim-type=\"\" data-anim-delay=\"0\">Building your own Recommendation System using a Simple Machine Learning<\/h2><\/div><\/div><\/div>[vc_column_text css=&#8221;.vc_custom_1655950364563{padding-top: 60px !important;padding-bottom: px !important;}&#8221;]<\/p>\r\n<p style=\"text-align: left;\">Now that we have talked about the two main techniques used in recommendation systems, we will discuss a simple way of creating one on your own using Machine Learning on Google Compute Engine. You can make use of open source technologies to create a basic recommendation system on the cloud platform.<\/p>\r\n<p>&nbsp;<\/p>\r\n<p style=\"text-align: left;\">A recommendation system consists of 4 phases: 1) collection, 2) storage, 3) analysis, and 4) recommendation. Its architecture consists of a front-end, a storage component, and Machine Learning. In the front-end, you can see a page with top recommendations by deploying a simple application on\u00a0<a class=\"au mn\" href=\"https:\/\/cloud.google.com\/appengine\/\" target=\"_blank\" rel=\"noopener ugc nofollow\">Google App Engine<\/a>. This will help you to build a scalable web platform. For storage,\u00a0<a class=\"au mn\" href=\"https:\/\/cloud.google.com\/sql\/\" target=\"_blank\" rel=\"noopener ugc nofollow\">Google Cloud SQL<\/a>\u00a0integrates well with\u00a0<a class=\"au mn\" href=\"http:\/\/spark.apache.org\/mllib\/\" target=\"_blank\" rel=\"noopener ugc nofollow\">MLlib<\/a>\u00a0which is a Machine Learning library. Lastly, you can use\u00a0<a class=\"au mn\" href=\"https:\/\/cloud.google.com\/dataproc\/\" target=\"_blank\" rel=\"noopener ugc nofollow\">Google Cloud Dataproc<\/a>\u00a0to deploy and run MLlib based scripts. For more on this, visit\u00a0<a class=\"au mn\" href=\"https:\/\/cloud.google.com\/blog\/products\/gcp\/how-to-build-your-own-recommendation-engine-using-machine-learning-on-google-compute-engine\" target=\"_blank\" rel=\"noopener ugc nofollow\">How to build your own recommendation engine using machine learning on Google Compute Engine<\/a><\/p>\r\n<p>[\/vc_column_text][\/vc_column][\/vc_row][\/vc_section][vc_row pix_particles_check=&#8221;&#8221;][vc_column]<div id=\"el1653971463480-ce74a014-4ae9\" class=\"w-100 d-block \"><\/div>[vc_column_text css=&#8221;.vc_custom_1655950422811{padding-top: 40px !important;padding-bottom: 0px !important;}&#8221;]To provide the perfect recommendation, your recommendation system needs lots and lots of data with high quality. Most times, it is very difficult for an individual or small- or medium-sized companies to collect such large quantity data while maintaining high quality. Therefore, it is often more efficient to find another service that does laborious works for you. We could be your perfect solution!<\/p>\r\n<p>&nbsp;<\/p>\r\n<p>Here at <strong><a class=\"au mn\" href=\"https:\/\/www.datumo.com\" target=\"_blank\" rel=\"noopener ugc nofollow\"><em class=\"pn\">D<\/em><\/a><\/strong><a href=\"https:\/\/www.datumo.com\"><strong>ATUMO<\/strong><\/a>, we crowdsource our tasks to diverse users located globally to ensure the quality and quantity on time. Moreover, our in-house managers double-check the quality of the collected or processed data. If you need data? If you need preprocessed data? Let us know![\/vc_column_text]<div id=\"el1653972293756-76a5ecd1-3d25\" class=\"w-100 d-block \"><\/div>[vc_column_text css=&#8221;.vc_custom_1655950394320{border-top-width: 1px !important;padding-top: 80px !important;padding-bottom: 0px !important;border-top-color: rgba(0,0,0,0.2) !important;border-top-style: solid !important;}&#8221;]To sum it all up, we started this tutorial by discussing what recommendation systems and what they are used for. We talked about some real-life examples where these systems are used e.g. by Facebook to suggest friends, by Netflix to recommend movies or shows, and by YouTube to recommend videos, etc. Then we discussed the techniques of Content-based filtering and Collaborative filtering that enable a recommendation system to do what it is supposed to do i.e. to make recommendations to users. We saw how the two techniques differed from each other, where one technique i.e. Content-based filtering, made suggestions on the basis of the user\u2019s profile whereas the other technique, Collaborative filtering, harnessed the judgment of other similar users to make recommendations to the user in question. Lastly, we briefly touched upon how one can build his\/her own recommendation system using Machine Learning on Google Compute Engine.[\/vc_column_text]<div id=\"el1653971463481-f4f34d7c-39ce\" class=\"w-100 d-block \"><\/div>[\/vc_column][\/vc_row][vc_row pix_particles_check=&#8221;&#8221;][vc_column width=&#8221;1\/2&#8243;]<div id=\"el1646794934167-c0c94dd3-ea74\" class=\"w-100 d-block \"><\/div><div class=\" mb-3 mb-md-0 \"  ><div class=\"card w-100 h-100 bg-white  vc_custom_1652982865548  pix-hover-item rounded-10 position-relative overflow-hidden2 text-white tilt fancy_card\" ><div class=\"card-img-overlay overflow-visible d-inline-block w-100 pix-img-overlay pix-p-30 d-flex align-items-end text-left\"><div class=\"w-100 \"><h3 class=\"card-title  text-black font-weight-bold mb-0 animate-in\" style=\"\">See what we can do for you.<\/h3><p class=\"card-text pix-pt-10 text-black \" style=\"\">Build smarter AI with us.<\/p><div class=\"card-btn-div mt-4 d-inline-block w-100\"><a  href=\"https:\/\/datumo.com\" class=\"btn mb-2     text-white btn-black d-inline-block      btn-md\" target=\"_blank\" rel=\"noopener\"    ><span class=\"font-weight-bold \" >Learn More<\/span><\/a><\/div><\/div><\/div><\/div><\/div>[\/vc_column][vc_column width=&#8221;1\/2&#8243;]<div id=\"el1646794982519-9a19190b-7fde\" class=\"w-100 d-block \"><\/div><div class=\" mb-3 mb-md-0 \"  ><div class=\"card w-100 h-100 bg-black  vc_custom_1653971438710  pix-hover-item rounded-10 position-relative overflow-hidden2 text-white tilt fancy_card\" ><div class=\"card-img-overlay overflow-visible d-inline-block w-100 pix-img-overlay pix-p-30 d-flex align-items-end text-left\"><div class=\"w-100 \"><h3 class=\"card-title  text-white font-weight-bold mb-0 animate-in\" style=\"\">We would like to support the AI industry by sharing.<\/h3><p class=\"card-text pix-pt-10 text-white \" style=\"\"><\/p><div class=\"card-btn-div mt-4 d-inline-block w-100\"><a  href=\"https:\/\/open.datumo.com\/en\" class=\"btn mb-2    vc_custom_1653971438714  btn-primary d-inline-block      btn-md\" target=\"_blank\" rel=\"noopener\"    ><span class=\"font-weight-bold \" >Download Open Datasets<\/span><\/a><\/div><\/div><\/div><\/div><\/div>[\/vc_column][\/vc_row][vc_row pix_particles_check=&#8221;&#8221;][vc_column]<div id=\"el1646799961152-e3ee06c0-4e82\" class=\"w-100 d-block \"><\/div>[\/vc_column][\/vc_row]<\/p>\r\n","protected":false},"excerpt":{"rendered":"[vc_row pix_particles_check=&#8221;&#8221;][vc_column][\/vc_column][\/vc_row][vc_row pix_particles_check=&#8221;&#8221;][vc_column][vc_column_text css=&#8221;.vc_custom_1655949926688{padding-top: 40px !important;padding-right: 20px !important;padding-bottom: 40px !important;padding-left: 20px !important;}&#8221;] We will talk about how to create a recommendation system with very little difficulty, but before that, we will talk about the different Machine Learning-based techniques used in&#8230;","protected":false},"author":1,"featured_media":16499,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[131],"tags":[26,127,150,209],"class_list":["post-16440","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tech","tag-ai","tag-datumo","tag-machine-learning","tag-recommendation-service"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v23.3 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Easiest Way to Create a Simple Recommendation Service - DATUMO<\/title>\n<meta name=\"description\" content=\"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/blog.datumo.com\/en\/tech\/16440\" \/>\n<meta property=\"og:locale\" content=\"ko_KR\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Easiest Way to Create a Simple Recommendation Service\" \/>\n<meta property=\"og:description\" content=\"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.\" \/>\n<meta property=\"og:url\" content=\"https:\/\/blog.datumo.com\/en\/tech\/16440\" \/>\n<meta property=\"og:site_name\" content=\"DATUMO\" \/>\n<meta property=\"article:published_time\" content=\"2022-06-23T02:00:48+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2024-10-22T09:02:18+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1092\" \/>\n\t<meta property=\"og:image:height\" content=\"728\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"DATUMO\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:title\" content=\"Easiest Way to Create a Simple Recommendation Service\" \/>\n<meta name=\"twitter:description\" content=\"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.\" \/>\n<meta name=\"twitter:image\" content=\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png\" \/>\n<meta name=\"twitter:label1\" content=\"\uae00\uc4f4\uc774\" \/>\n\t<meta name=\"twitter:data1\" content=\"DATUMO\" \/>\n\t<meta name=\"twitter:label2\" content=\"\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04\" \/>\n\t<meta name=\"twitter:data2\" content=\"10\ubd84\" \/>\n<script type=\"application\/ld+json\" class=\"yoast-schema-graph\">{\"@context\":\"https:\/\/schema.org\",\"@graph\":[{\"@type\":\"TechArticle\",\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440#article\",\"isPartOf\":{\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440\"},\"author\":{\"name\":\"DATUMO\",\"@id\":\"https:\/\/blog.datumo.com\/#\/schema\/person\/02ec2d0ba953b146878dab089dc735b6\"},\"headline\":\"Easiest Way to Create a Simple Recommendation Service\",\"datePublished\":\"2022-06-23T02:00:48+00:00\",\"dateModified\":\"2024-10-22T09:02:18+00:00\",\"mainEntityOfPage\":{\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440\"},\"wordCount\":2133,\"publisher\":{\"@id\":\"https:\/\/blog.datumo.com\/#organization\"},\"image\":{\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage\"},\"thumbnailUrl\":\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png\",\"keywords\":[\"AI\",\"datumo\",\"machine learning\",\"recommendation service\"],\"articleSection\":[\"tech\"],\"inLanguage\":\"ko-KR\"},{\"@type\":\"WebPage\",\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440\",\"url\":\"https:\/\/blog.datumo.com\/en\/tech\/16440\",\"name\":\"Easiest Way to Create a Simple Recommendation Service - DATUMO\",\"isPartOf\":{\"@id\":\"https:\/\/blog.datumo.com\/#website\"},\"primaryImageOfPage\":{\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage\"},\"image\":{\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage\"},\"thumbnailUrl\":\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png\",\"datePublished\":\"2022-06-23T02:00:48+00:00\",\"dateModified\":\"2024-10-22T09:02:18+00:00\",\"description\":\"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.\",\"breadcrumb\":{\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440#breadcrumb\"},\"inLanguage\":\"ko-KR\",\"potentialAction\":[{\"@type\":\"ReadAction\",\"target\":[\"https:\/\/blog.datumo.com\/en\/tech\/16440\"]}]},{\"@type\":\"ImageObject\",\"inLanguage\":\"ko-KR\",\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage\",\"url\":\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png\",\"contentUrl\":\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png\",\"width\":1092,\"height\":728},{\"@type\":\"BreadcrumbList\",\"@id\":\"https:\/\/blog.datumo.com\/en\/tech\/16440#breadcrumb\",\"itemListElement\":[{\"@type\":\"ListItem\",\"position\":1,\"name\":\"Home\",\"item\":\"https:\/\/blog.datumo.com\/en\/\"},{\"@type\":\"ListItem\",\"position\":2,\"name\":\"Easiest Way to Create a Simple Recommendation Service\"}]},{\"@type\":\"WebSite\",\"@id\":\"https:\/\/blog.datumo.com\/#website\",\"url\":\"https:\/\/blog.datumo.com\/\",\"name\":\"DATUMO\",\"description\":\"The Data for Smarter AI\",\"publisher\":{\"@id\":\"https:\/\/blog.datumo.com\/#organization\"},\"potentialAction\":[{\"@type\":\"SearchAction\",\"target\":{\"@type\":\"EntryPoint\",\"urlTemplate\":\"https:\/\/blog.datumo.com\/?s={search_term_string}\"},\"query-input\":\"required name=search_term_string\"}],\"inLanguage\":\"ko-KR\"},{\"@type\":\"Organization\",\"@id\":\"https:\/\/blog.datumo.com\/#organization\",\"name\":\"DATUMO\",\"url\":\"https:\/\/blog.datumo.com\/\",\"logo\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ko-KR\",\"@id\":\"https:\/\/blog.datumo.com\/#\/schema\/logo\/image\/\",\"url\":\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/05\/2.1.webp\",\"contentUrl\":\"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/05\/2.1.webp\",\"width\":1080,\"height\":600,\"caption\":\"DATUMO\"},\"image\":{\"@id\":\"https:\/\/blog.datumo.com\/#\/schema\/logo\/image\/\"}},{\"@type\":\"Person\",\"@id\":\"https:\/\/blog.datumo.com\/#\/schema\/person\/02ec2d0ba953b146878dab089dc735b6\",\"name\":\"DATUMO\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"ko-KR\",\"@id\":\"https:\/\/blog.datumo.com\/#\/schema\/person\/image\/\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/1942a8a63e1c8fa0d9be56cda789edd6c0a866259cd5dca24952597ffa8bab3d?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/1942a8a63e1c8fa0d9be56cda789edd6c0a866259cd5dca24952597ffa8bab3d?s=96&d=mm&r=g\",\"caption\":\"DATUMO\"},\"description\":\"DATUMO, The Data for Smarter AI. We seek to drive impact in the world by providing diverse and high quality data to build smarter AI.\",\"sameAs\":[\"https:\/\/blog.datumo.com\/en\"],\"url\":\"https:\/\/blog.datumo.com\/en\/author\/selectstar\"}]}<\/script>\n<!-- \/ Yoast SEO plugin. -->","yoast_head_json":{"title":"Easiest Way to Create a Simple Recommendation Service - DATUMO","description":"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.","robots":{"index":"index","follow":"follow","max-snippet":"max-snippet:-1","max-image-preview":"max-image-preview:large","max-video-preview":"max-video-preview:-1"},"canonical":"https:\/\/blog.datumo.com\/en\/tech\/16440","og_locale":"ko_KR","og_type":"article","og_title":"Easiest Way to Create a Simple Recommendation Service","og_description":"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.","og_url":"https:\/\/blog.datumo.com\/en\/tech\/16440","og_site_name":"DATUMO","article_published_time":"2022-06-23T02:00:48+00:00","article_modified_time":"2024-10-22T09:02:18+00:00","og_image":[{"width":1092,"height":728,"url":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png","type":"image\/png"}],"author":"DATUMO","twitter_card":"summary_large_image","twitter_title":"Easiest Way to Create a Simple Recommendation Service","twitter_description":"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.","twitter_image":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png","twitter_misc":{"\uae00\uc4f4\uc774":"DATUMO","\uc608\uc0c1 \ub418\ub294 \ud310\ub3c5 \uc2dc\uac04":"10\ubd84"},"schema":{"@context":"https:\/\/schema.org","@graph":[{"@type":"TechArticle","@id":"https:\/\/blog.datumo.com\/en\/tech\/16440#article","isPartOf":{"@id":"https:\/\/blog.datumo.com\/en\/tech\/16440"},"author":{"name":"DATUMO","@id":"https:\/\/blog.datumo.com\/#\/schema\/person\/02ec2d0ba953b146878dab089dc735b6"},"headline":"Easiest Way to Create a Simple Recommendation Service","datePublished":"2022-06-23T02:00:48+00:00","dateModified":"2024-10-22T09:02:18+00:00","mainEntityOfPage":{"@id":"https:\/\/blog.datumo.com\/en\/tech\/16440"},"wordCount":2133,"publisher":{"@id":"https:\/\/blog.datumo.com\/#organization"},"image":{"@id":"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage"},"thumbnailUrl":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png","keywords":["AI","datumo","machine learning","recommendation service"],"articleSection":["tech"],"inLanguage":"ko-KR"},{"@type":"WebPage","@id":"https:\/\/blog.datumo.com\/en\/tech\/16440","url":"https:\/\/blog.datumo.com\/en\/tech\/16440","name":"Easiest Way to Create a Simple Recommendation Service - DATUMO","isPartOf":{"@id":"https:\/\/blog.datumo.com\/#website"},"primaryImageOfPage":{"@id":"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage"},"image":{"@id":"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage"},"thumbnailUrl":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png","datePublished":"2022-06-23T02:00:48+00:00","dateModified":"2024-10-22T09:02:18+00:00","description":"There are two most common algorithms used for the recommendation system: Content-based filtering and Collaborative filtering.","breadcrumb":{"@id":"https:\/\/blog.datumo.com\/en\/tech\/16440#breadcrumb"},"inLanguage":"ko-KR","potentialAction":[{"@type":"ReadAction","target":["https:\/\/blog.datumo.com\/en\/tech\/16440"]}]},{"@type":"ImageObject","inLanguage":"ko-KR","@id":"https:\/\/blog.datumo.com\/en\/tech\/16440#primaryimage","url":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png","contentUrl":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/06\/assdf.png","width":1092,"height":728},{"@type":"BreadcrumbList","@id":"https:\/\/blog.datumo.com\/en\/tech\/16440#breadcrumb","itemListElement":[{"@type":"ListItem","position":1,"name":"Home","item":"https:\/\/blog.datumo.com\/en\/"},{"@type":"ListItem","position":2,"name":"Easiest Way to Create a Simple Recommendation Service"}]},{"@type":"WebSite","@id":"https:\/\/blog.datumo.com\/#website","url":"https:\/\/blog.datumo.com\/","name":"DATUMO","description":"The Data for Smarter AI","publisher":{"@id":"https:\/\/blog.datumo.com\/#organization"},"potentialAction":[{"@type":"SearchAction","target":{"@type":"EntryPoint","urlTemplate":"https:\/\/blog.datumo.com\/?s={search_term_string}"},"query-input":"required name=search_term_string"}],"inLanguage":"ko-KR"},{"@type":"Organization","@id":"https:\/\/blog.datumo.com\/#organization","name":"DATUMO","url":"https:\/\/blog.datumo.com\/","logo":{"@type":"ImageObject","inLanguage":"ko-KR","@id":"https:\/\/blog.datumo.com\/#\/schema\/logo\/image\/","url":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/05\/2.1.webp","contentUrl":"https:\/\/blog.datumo.com\/en\/wp-content\/uploads\/2022\/05\/2.1.webp","width":1080,"height":600,"caption":"DATUMO"},"image":{"@id":"https:\/\/blog.datumo.com\/#\/schema\/logo\/image\/"}},{"@type":"Person","@id":"https:\/\/blog.datumo.com\/#\/schema\/person\/02ec2d0ba953b146878dab089dc735b6","name":"DATUMO","image":{"@type":"ImageObject","inLanguage":"ko-KR","@id":"https:\/\/blog.datumo.com\/#\/schema\/person\/image\/","url":"https:\/\/secure.gravatar.com\/avatar\/1942a8a63e1c8fa0d9be56cda789edd6c0a866259cd5dca24952597ffa8bab3d?s=96&d=mm&r=g","contentUrl":"https:\/\/secure.gravatar.com\/avatar\/1942a8a63e1c8fa0d9be56cda789edd6c0a866259cd5dca24952597ffa8bab3d?s=96&d=mm&r=g","caption":"DATUMO"},"description":"DATUMO, The Data for Smarter AI. We seek to drive impact in the world by providing diverse and high quality data to build smarter AI.","sameAs":["https:\/\/blog.datumo.com\/en"],"url":"https:\/\/blog.datumo.com\/en\/author\/selectstar"}]}},"_links":{"self":[{"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/posts\/16440","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/comments?post=16440"}],"version-history":[{"count":9,"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/posts\/16440\/revisions"}],"predecessor-version":[{"id":16930,"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/posts\/16440\/revisions\/16930"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/media\/16499"}],"wp:attachment":[{"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/media?parent=16440"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/categories?post=16440"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/blog.datumo.com\/en\/wp-json\/wp\/v2\/tags?post=16440"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}