{"id":8108,"date":"2020-01-09T04:33:29","date_gmt":"2020-01-09T01:03:29","guid":{"rendered":"https:\/\/ahdsoft.ir\/recommender-systems\/"},"modified":"2024-10-13T15:38:03","modified_gmt":"2024-10-13T12:08:03","slug":"recommender-systems","status":"publish","type":"page","link":"https:\/\/ahdsoft.ir\/en\/services\/recommender-systems\/","title":{"rendered":"Recommender systems"},"content":{"rendered":"\t\t
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\r\n\t \t \/\/ About recommender systems<\/span>\r\n\t

Powerful guidance
\nFor smart choices<\/h2>\t <\/div>\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t01.<\/span>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Similar Products<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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\n\t\t\t\t\t02.<\/span>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Multi-Factor Similarity<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\n\t\t\t\t\t03.<\/span>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Personalized Recommender<\/h6>\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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\r\n\t\t\t01<\/span>\r\n\t\t\t
\r\n\t\t \t\t\t \t\t <\/span>\t <\/div>\r\n\t
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AI in Business<\/h5>\r\n\t

Implementation Consulting<\/p>\r\n\t <\/div>\r\n\t <\/div>\r\n\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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Artificial Intelligence<\/h5>\r\n\t

Learning and Evolution<\/p>\r\n\t <\/div>\r\n\t <\/div>\r\n\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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Business intelligence<\/h5>\r\n\t

Business Analysis<\/p>\r\n\t <\/div>\r\n\t <\/div>\r\n\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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\r\n\t \t \/\/ Recommendation System <\/span>\r\n\t

Why Recommendation Systems?\n<\/h2>\t <\/div>\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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Recommendation systems help users find the content they are looking for more quickly, significantly reducing the time spent searching for their favorite content. Moreover, by improving the user experience, they can assist businesses in enhancing their profitability. There are many advantages to using recommendation systems for businesses, some of which include:<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t

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  • Increase customer engagement<\/li>\r\n\t\t\t\t\t\t\t\t
  • Increase sales<\/li>\r\n\t\t\t\t\t\t\t\t
  • Reduce marketing costs<\/li>\r\n\t\t\t\t\t\t\t\t
  • Improved inventory management<\/li>\r\n\t\t\t\t\t\t\t\t
  • Improve customer satisfaction<\/li>\r\n\t\t\t\t\t\t\t\t
  • Helping the customer's decision making process<\/li>\r\n\t\t\t\t\t\t\t<\/ul>\r\n\t\t\t\t\t\t
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    Recommender systems can keep customers engaged by providing relevant and attractive content, thus increasing loyalty and repeat purchases.<\/p>\t\t\t<\/div>\r\n\t\t\t\t\t\t

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    Recommender systems can suggest personalized products or services based on customers' browsing or purchase history, which will lead to more sales for businesses.<\/p>\t\t\t<\/div>\r\n\t\t\t\t\t\t

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    By using recommender systems, businesses can reduce their marketing costs by targeting their resources to customers who are more likely to buy.<\/p>\t\t\t<\/div>\r\n\t\t\t\t\t\t

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    Recommender systems can help businesses manage inventory better. In this way, with the help of these systems, it is possible to predict the products that are likely to be in greater demand and ensure sufficient inventory to meet the customer's needs.<\/p>\t\t\t<\/div>\r\n\t\t\t\t\t\t

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    Customers will have a more satisfying experience if they receive personalized recommendations based on their interests and preferences.<\/p>\t\t\t<\/div>\r\n\t\t\t\t\t\t

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    Recommender systems can help users make more accurate decisions and not spend more time browsing through various products and services.<\/p>\t\t\t<\/div>\r\n\t\t\t\t <\/div>\r\n\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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    \r\n\t \t \/\/About Similar Products Recommender<\/span>\r\n\t

    Similar Products Recommender\n
    \nA Way to Experience More Variety<\/h2>\t <\/div>\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    This service utilizes AI algorithms and accesses product information to extract similarities between them, thereby suggesting similar products to the user. This way, users can engage more with other products, increasing the likelihood of purchases.<\/p>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t

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    \r\n\t \t \/\/ About Multi-Factor Recommender<\/span>\r\n\t

    Multi-Factor Recommender\n
    \nProvide Unique Suggestions Based on User Factors!<\/h2>\t <\/div>\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    \n\t\t\t\t\t\t\t\t\tOne of the challenges in recommendation systems is recognizing the interests of new users or obtaining explicit feedback from them. The multi-factor recommender provides a platform to identify the tastes and needs of users concerning products in the shortest time possible through a few key questions.\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t
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    \r\n\t \t \/\/ About Personalized Recommender<\/span>\r\n\t

    Personalized Recommender\n
    \nProduct Suggestions Based on Users' Tastes and Needs<\/h2>\t <\/div>\r\n\t \t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t
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    \n\t\t\t\t\t\t\t\t\tThis product by Ahad provides recommendations tailored to the taste and needs of each user based on their behavior history. This service can leverage various recorded information, such as user ratings, likes or dislikes, or even overall click patterns to learn and identify user preferences. Additionally, this service continuously tracks user behavior for updates, analyzing purchasing history and considering user-specific characteristics to suggest products tailored to each user.<\/div>\n<\/div>\n<\/div>\n<\/div>\t\t\t\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t
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    \/\/ About recommender systems Powerful guidance For smart choices 01. Similar Products 02. Multi-Factor Similarity 03. Personalized Recommender 01 AI in Business Implementation Consulting 02 Artificial Intelligence Learning and Evolution 03 Business intelligence Business Analysis \/\/ Recommendation System Why Recommendation Systems? Recommendation systems help users find the content they are looking for more quickly, significantly […]<\/p>\n","protected":false},"author":2,"featured_media":8112,"parent":8123,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-8108","page","type-page","status-publish","has-post-thumbnail","hentry"],"_links":{"self":[{"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/pages\/8108","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/comments?post=8108"}],"version-history":[{"count":13,"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/pages\/8108\/revisions"}],"predecessor-version":[{"id":8930,"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/pages\/8108\/revisions\/8930"}],"up":[{"embeddable":true,"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/pages\/8123"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/media\/8112"}],"wp:attachment":[{"href":"https:\/\/ahdsoft.ir\/en\/wp-json\/wp\/v2\/media?parent=8108"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}