TW201939378A - Resource recommendation method and device - Google Patents
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Abstract
Description
本申請涉及電腦技術領域，尤其涉及一種資源推薦方法及裝置。The present application relates to the field of computer technology, and in particular, to a resource recommendation method and device.
隨著網際網路技術的快速發展，基於網際網路技術的網路應用的種類和功能越來越豐富，網路應用可以向使用者推薦一些資源，例如，消費類應用可以向使用者推薦優惠券。隨著生活水準的不斷提高，使用者的需要也變得越來越多元化，因此，需要提出一種推薦效果更為精準的資源推薦方法，以滿足的使用者多元化需求。With the rapid development of Internet technology, the types and functions of Internet applications based on Internet technology are becoming more and more abundant. Network applications can recommend some resources to users. For example, consumer applications can recommend discounts to users. Coupons. With the continuous improvement of living standards, the needs of users have become more and more diversified. Therefore, it is necessary to propose a resource recommendation method with more accurate recommendation effects to meet the diverse needs of users.
本說明書實施例的目的是提供一種資源推薦方法及裝置，以達到能夠更為精準地向使用者推薦資源的目的。
為實現上述技術目的，本說明書實施例是這樣實現的：
第一方面，提供了一種資源推薦方法，所述方法包括：
當滿足預設資源推薦條件時，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊；
根據所述狀態資訊、所述使用者特徵資訊和所述人群類別資訊，判定與所述目標使用者匹配的待推薦資源；
向所述目標使用者推薦所述待推薦資源。
第二方面，提供了一種資源推薦裝置，所述裝置包括：
獲取單元，用於在滿足預設資源推薦條件的情況下，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊；
判定單元，用於根據所述狀態資訊、所述使用者特徵資訊和所述人群類別資訊，判定與所述目標使用者匹配的待推薦資源；
推薦單元，用於向所述目標使用者推薦所述待推薦資源。
第三方面，提供了一種電子設備，包括：
處理器；以及
被安排成儲存電腦可執行指令的記憶體，所述可執行指令在被執行時使所述處理器執行以下操作：
當滿足預設資源推薦條件時，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊；
根據所述狀態資訊、所述使用者特徵資訊和所述人群類別資訊，判定與所述目標使用者匹配的待推薦資源；
向所述目標使用者推薦所述待推薦資源。
第四方面，提供了一種電腦儲存媒體，所述電腦可讀儲存媒體儲存一個或多個程式，所述一個或多個程式當被包括多個應用程式的電子設備執行時，使得所述電子設備執行以下操作：
當滿足預設資源推薦條件時，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊；
根據所述狀態資訊、所述使用者特徵資訊和所述人群類別資訊，判定與所述目標使用者匹配的待推薦資源；
向所述目標使用者推薦所述待推薦資源。
由以上本說明書實施例提供的技術方案可見，本說明書實施例中，可以基於使用者的狀態資訊、使用者特徵和使用者所屬人群類別，向該使用者推薦相應的資源；由於使用者的狀態資訊、使用者特徵資訊以及使用者所屬人群類別可以從很大程度上反映該使用者的興趣和當前需求，因此，本說明書實施例可以實現資源的精準推薦，提高推薦效率。The purpose of the embodiments of the present specification is to provide a resource recommendation method and device, so as to achieve the purpose of more accurately recommending resources to users.
In order to achieve the above technical objectives, the embodiments of the present specification are implemented as follows:
In a first aspect, a resource recommendation method is provided. The method includes:
When the preset resource recommendation conditions are met, the status information of the target user, user characteristics information, and information about the category of the population to which the user belongs are obtained;
Determining, according to the status information, the user characteristic information, and the crowd category information, a resource to be recommended that matches the target user;
Recommending the resource to be recommended to the target user.
In a second aspect, a resource recommendation device is provided, where the device includes:
An obtaining unit, configured to obtain status information, user characteristic information, and category information of a target user when a preset resource recommendation condition is met;
A determining unit, configured to determine a resource to be recommended matching the target user according to the status information, the user characteristic information, and the crowd category information;
A recommendation unit, configured to recommend the resource to be recommended to the target user.
In a third aspect, an electronic device is provided, including:
A processor; and a memory arranged to store computer-executable instructions that, when executed, cause the processor to perform the following operations:
When the preset resource recommendation conditions are met, the status information of the target user, user characteristics information, and information about the category of the population to which the user belongs are obtained;
Determining, according to the status information, the user characteristic information, and the crowd category information, a resource to be recommended that matches the target user;
Recommending the resource to be recommended to the target user.
According to a fourth aspect, a computer storage medium is provided. The computer-readable storage medium stores one or more programs, and the one or more programs, when executed by an electronic device including a plurality of application programs, cause the electronic device to Do the following:
When the preset resource recommendation conditions are met, the status information of the target user, user characteristics information, and information about the category of the population to which the user belongs are obtained;
Determining, according to the status information, the user characteristic information, and the crowd category information, a resource to be recommended that matches the target user;
Recommending the resource to be recommended to the target user.
It can be seen from the technical solutions provided by the embodiments of the present specification that, in the embodiments of the present specification, the corresponding resources can be recommended to the user based on the user's status information, user characteristics, and user category; Information, user characteristic information, and categories of users to which the user belongs can largely reflect the user's interests and current needs. Therefore, the embodiments of this specification can achieve accurate resource recommendation and improve recommendation efficiency.
為了使本技術領域的人員更好地理解本說明書中的技術方案，下面將結合本說明書實施例中的附圖，對本說明書實施例中的技術方案進行清楚、完整地描述，顯然，所描述的實施例僅僅是本說明書一部分實施例，而不是全部的實施例。基於本說明書中的實施例，本領域普通技術人員在沒有做出創造性勞動前提下所獲得的所有其他實施例，都應當屬於本說明書保護的範圍。
本說明書實施例提供了一種資源推薦方法及裝置。
下面首先對本說明書實施例提供的一種資源推薦方法進行介紹。
需要說明的是，本說明書實施例提供的方法適用於伺服器，在實際應用中也可以適用於終端設備，例如智慧手機、平板電腦等等，本說明書實施例對此不作限定。
為了便於描述，下面以執行主體為伺服器對本說明書實施例技術方案進行介紹。
圖1是本說明書的一個實施例的資源推薦方法的流程圖，如圖1所示，該方法可以包括以下步驟：步驟102、步驟104和步驟106，其中，
在步驟102中，當滿足預設資源推薦條件時，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊。
本說明書實施例中，資源可以包括：與網路應用相關的資源，其中，與網路應用相關的資源可以包括：券、視頻、音訊等，券可以包括：消費抵用券、打折券等等。
本說明書實施例中，伺服器可以自發地主動向使用者推薦資源，也可以由使用者觸發伺服器向該使用者推薦資源。
本說明書實施例中，當伺服器自發地主動向使用者推薦資源時，在上述步驟102之前，可以增加以下步驟：當檢測到預設資源庫有更新時，判定滿足預設資源推薦條件。
本說明書實施例中，當由使用者觸發伺服器向該使用者推薦資源時，在上述步驟102之前，可以增加以下步驟：當監聽到目標使用者觸發的存取事件時，判定滿足預設資源推薦條件；其中，存取事件可以包括：打開特定應用程式、打開網頁或進行點擊等等。
本說明書實施例中，目標使用者的狀態資訊可以包括下述至少一種：目標使用者的當前所處位置、目標使用者當前所處位置的環境、目標使用者當前所處位置發生的事件、目標使用者預先指定的位置、目標使用者預先指定位置的環境和目標使用者預先指定位置發生的事件；其中，環境可以包括：天氣、空氣品質等，事件可以包括：大型節日活動、促銷活動等，使用者預先指定的位置可以包括：使用者出差地、出遊地等。
本說明書實施例中，可以預先收集各使用者的歷史行為，對各使用者的歷史行為進行分析，例如使用機器學習模型進行分析，得到各使用者的使用者特徵，建立使用者標識與使用者特徵的對應關係，並保存。在此情況下，可以通過以下方式獲取目標使用者的使用者特徵資訊：獲取目標使用者的使用者標識資訊，根據目標使用者的使用者標識資訊，以及預先建立的使用者標識與使用者特徵的對應關係，獲取與目標使用者的使用者標識資訊對應的使用者特徵資訊。
本說明書實施例中，還可以在判定滿足預設資源推薦條件時，收集目標使用者的歷史行為，對收集到的目標使用者的歷史行為進行分析，得到目標使用者的使用者特徵資訊。
需要說明的是，本說明書實施例中，使用者標識資訊為用於唯一標識使用者的資訊。使用者特徵資訊可以理解為使用者畫像，例如使用者的行為習慣、興趣偏好等。
本說明書實施例中，可以預先收集各使用者的存取事件，對各使用者的存取事件進行分析，將使用者劃分為幾個人群類別，例如，按照消費特點，劃分為：平實型消費人群、潛力消費人群、消極消費人群、實力消費人群、中堅消費人群、弱勢消費人群和經濟型消費人群等。之後建立使用者標識與人群類別的對應關係，並保存。在此情況下，可以通過以下方式獲取目標使用者所屬的人群類別資訊：
獲取目標使用者的使用者標識資訊，根據目標使用者的使用者標識資訊，以及預先建立的使用者標識與人群類別的對應關係，獲取與目標使用者的使用者標識資訊對應的人群類別資訊。
在步驟104中，根據目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊，判定與目標使用者匹配的待推薦資源。
本說明書實施例中，可以同時結合目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊，判定待推薦資源。例如，首先使用目標使用者的狀態資訊，從預設資源庫中篩選出一部分資源（稱為「第一備選資源集合」），之後使用目標使用者的使用者特徵資訊，從第一備選資源集合中進一步篩選出一部分資源（稱為「第二備選資源集合」），最後使用目標使用者所屬的人群類別資訊，從第二備選資源集合中篩選出待推薦資源。
本說明書實施例中，可以分別依據目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊，判定待推薦資源。例如，依據目標使用者的狀態資訊和使用者特徵資訊，判定與目標使用者匹配的第一類待推薦資源；依據目標使用者所屬的人群類別資訊，判定與目標使用者匹配的第二類待推薦資源；由第一類待推薦資源和第二類待推薦資源構成最終的待推薦資源。
在步驟106中，向目標使用者推薦待推薦資源。
本說明書實施例中，可以將待推薦資源進行排序，之後將排序結果推送給目標使用者，以實現向目標使用者推薦待推薦資源。
由上述實施例可見，該實施例中，可以基於使用者的狀態資訊、使用者特徵和使用者所屬人群類別，向該使用者推薦相應的資源；由於使用者的狀態資訊、使用者特徵資訊以及使用者所屬人群類別可以從很大程度上反映該使用者的興趣和當前需求，因此，本說明書實施例可以實現資源的精準推薦，提高推薦效率。
圖2是本說明書的另一個實施例的資源推薦方法的流程圖，在分別依據目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊，判定待推薦資源的情況下，如圖2所示，該方法可以包括以下步驟：
在步驟202中，當滿足預設資源推薦條件時，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊。
本說明書實施例中的步驟202與圖1所示實施例中的步驟102類似，在此不再贅述，詳情請見圖1所示實施例中的內容。
在步驟204中，根據目標使用者的狀態資訊和使用者特徵資訊，判定與目標使用者匹配的第一類待推薦資源。
本說明書實施例中，第一類待推薦資源為基於目標使用者的狀態資訊和使用者特徵判定的資源，第二類待推薦資源為基於目標使用者所屬的人群類別資訊判定的資源，其中，第一類待推薦資源中可以包括：一個或多個資源，第二類待推薦資源中可以包括：一個或多個資源。
本說明書實施例中，可以同時基於目標使用者的狀態資訊和使用者特徵資訊，判定與目標使用者匹配的第一類待推薦資源，此時，上述步驟204可以包括以下步驟：步驟2041和步驟2042，其中，
在步驟2041中，根據目標使用者的狀態資訊和使用者特徵資訊，產生用於描述目標使用者的上下文資訊。
本說明書實施例中，上下文資訊可以理解為「使用者標籤」，用於描述目標使用者的狀態和特徵。
在步驟2042中，根據目標使用者的上下文資訊檢索預設資源庫，獲得與目標使用者的上下文資訊匹配的第一類待推薦資源。
本說明書實施例中，可以預先建立使用者的上下文資訊與預設資源庫中儲存的資源的對應關係，之後根據該對應關係以及目標使用者的上下文資訊，從預設資源庫中獲得與目標使用者的上下文資訊匹配的第一類待推薦資源。
在一個例子中，以券為例，根據目標使用者的即時狀態和使用者特徵，產生目標使用者的上下文資訊，基於該上下文資訊以及預先建立的使用者上下文與券的對應關係，檢索用於儲存券的資料庫，獲得與該上下文資訊匹配的券。
在步驟206中，根據目標使用者的人群類別資訊，判定與目標使用者匹配的第二類待推薦資源。
本說明書實施例中，可以預先建立人群類別與資源的對應關係，之後依據該對應關係及目標使用者的人群類別資訊，判定與目標使用者匹配的第二類待推薦資源。
在步驟208中，對第一類待推薦資源和第二類待推薦資源進行排序，並將排序結果推薦給目標使用者。
本說明書實施例中，排序結果可以包括：資源的推薦順序。排序結果的推薦方式可以包括：通過清單的方式推薦，該清單中顯示有多個資源，清單中的資源按照某種規則進行排序；或者該排序結果的推薦方式可以包括：按照某種順序逐個推送每個資源。
本說明書實施例中，可以將第一類待推薦資源和第二類待推薦資源進行混合排序，也可以對第一類待推薦資源和第二類待推薦資源進行分別排序。
本說明書實施例中，當將第一類待推薦資源和第二類待推薦資源進行混合排序時，上述步驟208可以包括以下步驟：對第一類待推薦資源和第二類待推薦資源進行混合排序，並將混合排序結果推薦給目標使用者。
本說明書實施例中，當第一類待推薦資源中的資源，與第二類待推薦資源中的資源完全不同時，可以選擇將第一類待推薦資源排在前面，而將第二類待推薦資源排在後面；或者，可以選擇將第二類待推薦資源排在前面，而將第一類待推薦資源排在後面；或者，可以按照資源的屬性（例如券的金額或券的折扣力度），對第一類待推薦資源和第二類待推薦資源進行混合排序。
當第一類待推薦資源中的資源，與第二類待推薦資源中的資源部分相同時，首先進行去重操作（即將重複的資源只推薦一次），之後，將重複的資源排在前面，而將未重複的資源排在後面。
當第一類待推薦資源中的資源，與第二類待推薦資源中的資源完全相同時，可以按照資源的屬性（例如券的金額或折扣力度），對待推薦資源進行排序，其中，重複的資源只推薦一次。
本說明書實施例中，當對第一類待推薦資源和第二類待推薦資源進行分別排序時，上述步驟208可以包括以下步驟：步驟2081、步驟2082和步驟2083，其中，
在步驟2081中，對第一類待推薦資源中的資源進行排序，得到第一排序結果。
在一個例子中，第一類待推薦資源包括：券1、券2、券3和券4，本步驟中，對券1、券2、券3和券4進行排序，例如，第一排序結果為：推薦順序依次是券1、券2、券3和券4。
在步驟2082中，對第二類待推薦資源中的資源進行排序，得到第二排序結果。
在一個例子中，第二類待推薦資源包括：券6、券7、券8和券9，本步驟中，對券6、券7、券8和券9進行排序，例如，第二排序結果為：推薦順序依次是券6、券7、券8和券9。
在步驟2083中，分別將第一排序結果和第二排序結果推薦給目標使用者。
本說明書技術方案可以應用於行銷系統中，該行銷系統可以同時基於人群分類後按照分類實施行銷和基於使用者即時狀態實施行銷，例如用於券的發放，為了便於理解，圖3示出了應用本方案的行銷系統，該行銷系統中包括：人群召回模組、人群類別儲存系統、人群分類模組、事件訊息佇列、券庫；以及使用者即時狀態獲取模組、標籤召回模組、使用者特徵儲存系統、券儲存系統和排序推薦模組。
該行銷系統可以包括兩條鏈路，第一條鏈路由人群召回模組、人群類別儲存系統、人群分類模組、事件訊息佇列和券庫構成；其中，事件訊息佇列用於儲存海量使用者的點擊、搜索及支付等事件，並將海量使用者的事件發送給人群分類模組；人群分類模組用於根據事件訊息佇列中的事件將海量使用者劃分為幾個人群類別，並將劃分得到的人群類別告知人群類別儲存系統；券庫用於儲存券，並將儲存的券的資訊告知人群類別儲存系統；人群類別儲存系統用於儲存人群類別與券的對應關係；以上過程均通過離線操作實現；
當使用者A存取時，人群召回模組獲取使用者A所屬的人群類別，並從人群類別儲存系統中獲取人群類別與券的對應關係，根據使用者A所屬的人群類別以及該對應關係，判定與使用者A所屬的人群類別對應的券。
第二條鏈路由使用者即時狀態獲取模組、標籤召回模組、使用者特徵儲存系統、券儲存系統構成；其中，券儲存系統用於儲存券，使用者特徵儲存系統用於儲存使用者的使用者特徵；當使用者A存取時，使用者即時狀態獲取模組獲取使用者A的即時狀態資訊（例如，獲取即時位置及位置對應的天氣、商機等），併發送給標籤召回模組；標籤召回模組從使用者特徵儲存系統中獲取使用者A的使用者特徵資訊，並將使用者A的即時狀態資訊和使用者特徵資訊合起來形成使用者A的上下文資訊，再用上下文資訊檢索券儲存系統，判定與使用者A的上下文資訊對應的券。
排序推薦模組將人群召回模組判定的與使用者A所屬的人群類別對應的券和簽召回模組判定的與使用者A的上下文資訊對應的券進行排序，排序後按照順序返回給使用者A。
可見，基於本技術方案的行銷系統中，兩條鏈路可以複用排序推薦模組。
本說明書實施例中，基於本技術方案的行銷系統中即時人群和即時狀態的整合推薦，提升在推薦行銷當中的券推薦方式，進而提升與使用者相關的召回券資料，從中再選出使用者感興趣的券，提升整體的推薦效率。
由上述實施例可見，該實施例中，可以基於使用者的狀態資訊和使用者特徵，向該使用者推薦相應的資源；同時也可以基於使用者所屬人群類別，向該使用者推薦相應的資源，即可以實現同時支援兩種資源推薦方式；此外，由於使用者的狀態資訊、使用者特徵資訊以及使用者所屬人群類別可以從很大程度上反映該使用者的興趣和當前需求，因此本說明書實施例可以實現資源的精準推薦，提高推薦效率。
圖4是本說明書的一個實施例的資源推薦裝置的結構示意圖，如圖4所示，在一種軟體實施方式中，資源推薦裝置400可以包括：獲取單元401、判定單元402和推薦單元403，其中，
獲取單元401，用於在滿足預設資源推薦條件的情況下，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊；
判定單元402，用於根據所述狀態資訊、所述使用者特徵資訊和所述人群類別資訊，判定與所述目標使用者匹配的待推薦資源；
推薦單元403，用於向所述目標使用者推薦所述待推薦資源。
由上述實施例可見，該實施例中，可以基於使用者的狀態資訊、使用者特徵和使用者所屬人群類別，向該使用者推薦相應的資源；由於使用者的狀態資訊、使用者特徵資訊以及使用者所屬人群類別可以從很大程度上反映該使用者的興趣和當前需求，因此本說明書實施例可以實現資源的精準推薦，提高推薦效率。
可選的，作為一個實施例，所述判定單元402，可以包括：
第一資源判定子單元，用於根據所述狀態資訊和所述使用者特徵資訊，判定與所述目標使用者匹配的第一類待推薦資源；以及
第二資源判定子單元，用於根據所述人群類別資訊，判定與所述目標使用者匹配的第二類待推薦資源。
可選的，作為一個實施例，所述第一資源判定子單元，可以包括：
上下文資訊產生子單元，用於根據所述狀態資訊和所述使用者特徵資訊，產生用於描述所述目標使用者的上下文資訊；
第一類待推薦資源判定子單元，用於根據所述上下文資訊檢索預設資源庫，獲得與所述上下文資訊匹配的第一類待推薦資源。
可選的，作為一個實施例，所述推薦單元403，可以包括：
第一排序子單元，用於對所述第一類待推薦資源和所述第二類待推薦資源進行混合排序，得到混合排序結果；
第一推薦子單元，用於將所述混合排序結果推薦給所述目標使用者。
可選的，作為一個實施例，所述推薦單元403，可以包括：
第二排序子單元，用於對所述第一類待推薦資源中的資源進行排序，得到第一排序結果；以及
第三排序子單元，用於對所述第二類待推薦資源中的資源進行排序，得到第二排序結果；
第二推薦子單元，用於分別將所述第一排序結果和所述第二排序結果推薦給所述目標使用者。
可選的，作為一個實施例，所述資源推薦裝置400，還可以包括：
檢測單元，用於在檢測到預設資源庫有更新的情況下，判定滿足所述預設資源推薦條件；或者，
監聽單元，用於在監聽到所述目標使用者觸發的存取事件的情況下，判定滿足所述預設資源推薦條件。
可選的，作為一個實施例，所述狀態資訊可以包括下述至少一種：
所述目標使用者的當前所處位置、所述目標使用者當前所處位置的環境、所述目標使用者當前所處位置發生的事件、所述目標使用者預先指定的位置、所述目標使用者預先指定位置的環境和所述目標使用者預先指定位置發生的事件。
資源推薦裝置400還可執行圖1所示實施例的方法，並實現資源推薦裝置在圖4所示實施例的功能，本說明書實施例在此不再贅述。
圖5是本說明書的一個實施例的電子設備的結構示意圖，如圖5所示，在硬體層面，該電子設備包括處理器，可選地還包括內部匯流排、網路介面、記憶體。其中，記憶體可能包含記憶體，例如高速隨機存取記憶體（Random-Access Memory，RAM），也可能還包括非揮發性記憶體（non-volatile memory），例如至少1個磁碟記憶體等。當然，該電子設備還可能包括其他業務所需要的硬體。
處理器、網路介面和記憶體可以通過內部匯流排相互連接，該內部匯流排可以是ISA（Industry Standard Architecture，工業標準架構）匯流排、PCI（Peripheral Component Interconnect，周邊設備組件互連標準）匯流排或EISA（Extended Industry Standard Architecture，延伸工業標準架構）匯流排等。所述匯流排可以分為位址匯流排、資料匯流排、控制匯流排等。為便於表示，圖5中僅用一個雙向箭頭表示，但並不表示僅有一根匯流排或一種類型的匯流排。
記憶體，用於存放程式。具體地，程式可以包括程式碼，所述程式碼包括電腦操作指令。記憶體可以包括記憶體和非揮發性記憶體，並向處理器提供指令和資料。
處理器從非揮發性記憶體中讀取對應的電腦程式到記憶體中然後運行，在邏輯層面上形成資源推薦裝置。處理器，執行記憶體所存放的程式，並具體用於執行以下操作：
當滿足預設資源推薦條件時，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊；
根據所述狀態資訊、所述使用者特徵資訊和所述人群類別資訊，判定與所述目標使用者匹配的待推薦資源；
向所述目標使用者推薦所述待推薦資源。
上述如本說明書圖5所示實施例揭示的資源推薦裝置執行的方法可以應用於處理器中，或者由處理器實現。處理器可能是一種積體電路晶片，具有信號的處理能力。在實現過程中，上述方法的各步驟可以通過處理器中的硬體的集成邏輯電路或者軟體形式的指令完成。上述的處理器可以是通用處理器，包括中央處理器（Central Processing Unit，CPU）、網路處理器（Network Processor，NP）等；還可以是數位訊號處理器（Digital Signal Processor，DSP）、專用積體電路（Application Specific Integrated Circuit，ASIC）、現場可程式設計閘陣列（Field-Programmable Gate Array，FPGA）或者其他可程式設計邏輯裝置、閘門或者電晶體邏輯裝置、閘硬體元件。可以實現或者執行本說明書實施例中的公開的各方法、步驟及邏輯方塊圖。通用處理器可以是微處理器或者該處理器也可以是任何常規的處理器等。結合本說明書實施例所公開的方法的步驟可以直接體現為硬體解碼處理器執行完成，或者用解碼處理器中的硬體及軟體模組組合執行完成。軟體模組可以位於隨機記憶體，快閃記憶體、唯讀記憶體，可程式設計唯讀記憶體或者電可讀寫可程式設計記憶體、寄存器等本領域成熟的儲存媒體中。該儲存媒體位於記憶體，處理器讀取記憶體中的資訊，結合其硬體完成上述方法的步驟。
該電子設備還可執行圖1的方法，並實現資源推薦裝置在圖1所示實施例的功能，本說明書實施例在此不再贅述。
當然，除了軟體實現方式之外，本說明書的電子設備並不排除其他實現方式，比如邏輯裝置抑或軟硬體結合的方式等等，也就是說以下處理流程的執行主體並不限定於各個邏輯單元，也可以是硬體或邏輯裝置。
本說明書實施例還提出了一種電腦可讀儲存媒體，該電腦可讀儲存媒體儲存一個或多個程式，該一個或多個程式包括指令，該指令當被包括多個應用程式的可擕式電子設備執行時，能夠使該可擕式電子設備執行圖1所示實施例的方法，並具體用於執行以下方法：
當滿足預設資源推薦條件時，獲取目標使用者的狀態資訊、使用者特徵資訊和所屬的人群類別資訊；
根據所述狀態資訊、所述使用者特徵資訊和所述人群類別資訊，判定與所述目標使用者匹配的待推薦資源；
向所述目標使用者推薦所述待推薦資源。
總之，以上所述僅為本說明書的較佳實施例而已，並非用於限定本說明書的保護範圍。凡在本說明書的精神和原則之內，所作的任何修改、等同替換、改進等，均應包含在本說明書的保護範圍之內。
上述實施例闡明的系統、裝置、模組或單元，具體可以由電腦晶片或實體實現，或者由具有某種功能的產品來實現。一種典型的實現設備為電腦。具體的，電腦例如可以為個人電腦、膝上型電腦、蜂窩電話、相機電話、智慧型電話、個人數位助理、媒體播放機、導航設備、電子郵件設備、遊戲控制台、平板電腦、可穿戴設備或者這些設備中的任何設備的組合。
電腦可讀媒體包括永久性和非永久性、可移動和非可移動媒體可以由任何方法或技術來實現資訊儲存。資訊可以是電腦可讀指令、資料結構、程式的模組或其他資料。電腦的儲存媒體的例子包括，但不限於相變記憶體(PRAM)、靜態隨機存取記憶體(SRAM)、動態隨機存取記憶體(DRAM)、其他類型的隨機存取記憶體(RAM)、唯讀記憶體(ROM)、電可擦除可程式設計唯讀記憶體(EEPROM)、快閃記憶體或其他記憶體技術、唯讀光碟唯讀記憶體(CD-ROM)、數位多功能光碟(DVD)或其他光學儲存、磁盒式磁帶，磁帶磁磁片儲存或其他磁性存放裝置或任何其他非傳輸媒體，可用於儲存可以被計算設備存取的資訊。按照本文中的界定，電腦可讀媒體不包括暫存電腦可讀媒體(transitory media)，如調製的資料信號和載波。
還需要說明的是，術語「包括」、「包含」或者其任何其他變體意在涵蓋非排他性的包含，從而使得包括一系列要素的過程、方法、商品或者設備不僅包括那些要素，而且還包括沒有明確列出的其他要素，或者是還包括為這種過程、方法、商品或者設備所固有的要素。在沒有更多限制的情況下，由語句「包括一個……」限定的要素，並不排除在包括所述要素的過程、方法、商品或者設備中還存在另外的相同要素。
本說明書中的各個實施例均採用遞進的方式描述，各個實施例之間相同相似的部分互相參見即可，每個實施例重點說明的都是與其他實施例的不同之處。尤其，對於系統實施例而言，由於其基本相似於方法實施例，所以描述的比較簡單，相關之處參見方法實施例的部分說明即可。In order to enable those skilled in the art to better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present specification. Obviously, the described The examples are only a part of examples of this specification, but not all examples. Based on the embodiments in this specification, all other embodiments obtained by a person of ordinary skill in the art without creative efforts should fall within the protection scope of this specification.
The embodiments of the present specification provide a resource recommendation method and device.
The following first introduces a resource recommendation method provided by an embodiment of the present specification.
It should be noted that the method provided in the embodiment of the present specification is applicable to a server, and can also be applied to a terminal device, such as a smart phone, a tablet computer, etc. in an actual application, which is not limited in the embodiment of the present specification.
For the convenience of description, the technical solution of the embodiment of the present specification is described below with the execution subject as a server.
FIG. 1 is a flowchart of a resource recommendation method according to an embodiment of the present specification. As shown in FIG. 1, the method may include the following steps: step 102, step 104, and step 106, where:
In step 102, when the preset resource recommendation condition is satisfied, status information of the target user, user characteristic information, and information about the category of the population to which the target user belongs are obtained.
In the embodiment of the present specification, the resources may include resources related to network applications. Among them, the resources related to network applications may include coupons, videos, audios, etc. The coupons may include consumption coupons, discount coupons, etc. .
In the embodiment of the present specification, the server can actively recommend resources to the user spontaneously, or the user can trigger the server to recommend resources to the user.
In the embodiment of the present specification, when the server actively recommends resources to the user spontaneously, before the above step 102, the following steps may be added: when it is detected that the preset resource library is updated, it is determined that the preset resource recommendation condition is satisfied.
In the embodiment of the present specification, when a server is triggered by a user to recommend a resource to the user, before the above step 102, the following steps may be added: when the access event triggered by the target user is monitored, it is determined that the preset resource is satisfied. Recommended conditions; among them, the access event can include: opening a specific application, opening a web page, clicking, etc.
In the embodiment of the present specification, the status information of the target user may include at least one of the following: the current position of the target user, the environment of the current position of the target user, an event occurring at the current position of the target user, and the target Locations pre-designated by the user, environment pre-designated by the target user, and events occurring in the position pre-designated by the target user; the environment may include: weather, air quality, etc. The events may include: large-scale festivals, promotions, etc. The locations specified by the user in advance may include: places where the user travels, travels, and the like.
In the embodiment of the present specification, the historical behavior of each user can be collected in advance, and the historical behavior of each user can be analyzed, for example, using a machine learning model to analyze, to obtain the user characteristics of each user, and to establish a user identification and a user. Correspondence between features and save. In this case, the user characteristics information of the target user can be obtained by: obtaining the user identification information of the target user, according to the user identification information of the target user, and the pre-established user identification and user characteristics To obtain user characteristic information corresponding to the user identification information of the target user.
In the embodiment of the present specification, when it is determined that the preset resource recommendation condition is satisfied, the historical behavior of the target user is collected, and the historical behavior of the collected target user is analyzed to obtain the user characteristic information of the target user.
It should be noted that, in the embodiment of the present specification, the user identification information is information for uniquely identifying the user. User characteristic information can be understood as user portraits, such as user behaviors, interests and preferences.
In the embodiment of the present specification, the access events of each user can be collected in advance, the access events of each user can be analyzed, and the users can be divided into several groups of people. For example, according to consumption characteristics, it can be divided into: level consumption Crowds, potential consumers, negative consumers, strong consumers, backbone consumers, vulnerable consumers, and economic consumers. After that, the correspondence between the user identification and the crowd category is established and saved. In this case, you can obtain the category information of the target user in the following ways:
Acquire the user identification information of the target user, and obtain the crowd type information corresponding to the user identification information of the target user according to the user identification information of the target user and the pre-established correspondence between the user identification and the crowd type.
In step 104, a resource to be recommended matching the target user is determined according to the status information of the target user, user characteristic information, and information about the category of the population to which the target user belongs.
In the embodiment of the present specification, the status information of the target user, the user characteristic information, and the category information of the group to which the user belongs can be used to determine the resource to be recommended. For example, first use the status information of the target user to filter out some resources from the preset resource library (called the "first candidate resource set"), and then use the user characteristic information of the target user to A part of the resources are further screened out in the resource set (referred to as a "second alternative resource set"), and finally, the category information of the target user is used to filter out resources to be recommended from the second alternative resource set.
In the embodiment of the present specification, the resources to be recommended may be determined according to the status information of the target user, user characteristic information, and information of the category of the population to which the user belongs. For example, the first type of resources to be recommended matching the target user is determined based on the status information and user characteristic information of the target user; the second type of resources to be matched with the target user are determined based on the category information of the target user to which the target user belongs. Recommended resources; the first type of resources to be recommended and the second type of resources to constitute the final resource to be recommended.
In step 106, a resource to be recommended is recommended to the target user.
In the embodiment of the present specification, the resources to be recommended can be sorted, and then the sorting result is pushed to the target user, so as to realize recommending the resources to be recommended to the target user.
It can be seen from the above embodiment that in this embodiment, a user can be recommended to a corresponding resource based on the user's status information, user characteristics, and the type of crowd to which the user belongs; due to the user's status information, user characteristics information, and The category of the crowd to which a user belongs can largely reflect the user's interests and current needs. Therefore, the embodiments of this specification can achieve accurate recommendation of resources and improve recommendation efficiency.
FIG. 2 is a flowchart of a resource recommendation method according to another embodiment of the present specification. In the case of determining a resource to be recommended according to the status information of the target user, the user characteristic information, and the category information of the belonging user, as shown in FIG. 2 As shown, the method can include the following steps:
In step 202, when the preset resource recommendation condition is met, status information of the target user, user characteristic information, and information about the category of the population to which the target user belongs are obtained.
Step 202 in the embodiment of the present specification is similar to step 102 in the embodiment shown in FIG. 1, and details are not described herein again. For details, refer to the content in the embodiment shown in FIG. 1.
In step 204, the first type of resources to be recommended matching the target user is determined according to the status information and user characteristic information of the target user.
In the embodiment of the present specification, the first type of resources to be recommended are resources determined based on the status information and user characteristics of the target user, and the second type of resources to be recommended are resources determined based on the category information of the target user. The first type of resources to be recommended may include: one or more resources, and the second type of resources to be recommended may include: one or more resources.
In the embodiment of the present specification, the first type of resources to be recommended matching the target user may be determined based on the status information and user characteristic information of the target user at this time. At this time, the above step 204 may include the following steps: step 2041 and step 2042, of which
In step 2041, context information for describing the target user is generated according to the status information and user characteristic information of the target user.
In the embodiment of the present specification, the context information can be understood as a “user tag”, which is used to describe the status and characteristics of the target user.
In step 2042, the preset resource library is retrieved according to the context information of the target user to obtain the first type of resources to be recommended that match the context information of the target user.
In the embodiment of the present specification, the correspondence between the user's context information and the resources stored in the preset resource library can be established in advance, and then the target use is obtained from the preset resource library according to the correspondence relationship and the context information of the target user. The first type of to-be-recommended resource matches the context information of the user.
In one example, taking the coupon as an example, the context information of the target user is generated according to the real-time status and user characteristics of the target user. Based on the context information and the pre-established correspondence between the user context and the coupon, the search for Database of stored vouchers to get vouchers that match that contextual information.
In step 206, according to the category information of the target user, a second type of resources to be recommended matching the target user is determined.
In the embodiment of the present specification, a correspondence relationship between a crowd type and a resource may be established in advance, and then a second type of resource to be recommended matching the target user is determined according to the correspondence relationship and the crowd type information of the target user.
In step 208, the first type of resources to be recommended and the second type of resources to be recommended are sorted, and the ranking results are recommended to the target user.
In the embodiment of the present specification, the ranking result may include: a recommended order of resources. The recommendation method of ranking results may include: recommending through a list, where multiple resources are displayed in the list, and the resources in the list are sorted according to a certain rule; or the recommendation method of the ranking results may include: pushing one by one in a certain order Every resource.
In the embodiment of the present specification, the resources of the first type to be recommended and the resources of the second type to be recommended may be mixed, and the resources of the first type to be recommended and the resources of the second type to be recommended may be separately sorted.
In the embodiment of the present specification, when the first type of resources to be recommended and the second type of resources to be recommended are mixed and sorted, the above step 208 may include the following steps: mixing the first type of resources to be recommended and the second type of resources to be recommended Sort, and recommend mixed sorted results to target users.
In the embodiment of the present specification, when the resources in the first type of resources to be recommended are completely different from the resources in the second type of resources to be recommended, the first type of resources to be recommended may be selected to be ranked first, and the second type of resources to be recommended may be selected first. Recommended resources are ranked behind; or, you can choose to rank the second category of resources to be recommended first and the first category of resources to be recommended behind; or you can follow the attributes of the resources (such as the amount of coupons or discount strength of coupons) ) To perform a hybrid ranking on the first type of resources to be recommended and the second type of resources to be recommended.
When the resources in the first type of resources to be recommended are the same as those in the second type of resources to be recommended, the deduplication operation is performed first (repeated resources are recommended only once), and then the repeated resources are ranked first. The non-repeated resources are ranked behind.
When the resources in the first type of resources to be recommended are exactly the same as those in the second type of resources to be recommended, the recommended resources can be sorted according to the attributes of the resources (such as the amount of coupons or discount strength). Resources are only recommended once.
In the embodiment of the present specification, when the first type of resources to be recommended and the second type of resources to be recommended are sorted separately, the above step 208 may include the following steps: step 2081, step 2082, and step 2083, where:
In step 2081, resources in the first type of resources to be recommended are sorted to obtain a first ranking result.
In an example, the first type of resources to be recommended includes: coupon 1, coupon 2, coupon 3, and coupon 4. In this step, the coupon 1, coupon 2, coupon 3, and coupon 4 are sorted. For example, the first ranking result For: The recommended order is coupon 1, coupon 2, coupon 3, and coupon 4.
In step 2082, resources in the second type of resources to be recommended are sorted to obtain a second ranking result.
In an example, the second type of resources to be recommended includes: coupon 6, coupon 7, coupon 8, and coupon 9. In this step, the coupon 6, coupon 7, coupon 8, and coupon 9 are sorted, for example, the second sorting result For: The recommended order is coupon 6, coupon 7, coupon 8, and coupon 9, in that order.
In step 2083, the first ranking result and the second ranking result are recommended to the target user, respectively.
The technical solution of this specification can be applied to a marketing system. The marketing system can simultaneously implement marketing based on the classification of the crowd and marketing based on the user's real-time status, for example, for issuing coupons. For easy understanding, Figure 3 shows the application The marketing system of this solution, the marketing system includes: a crowd recall module, a crowd category storage system, a crowd classification module, an event message queue, a voucher; and a user's real-time status acquisition module, a tag recall module, and use User feature storage system, coupon storage system, and ranking recommendation module.
The marketing system can include two links. The first link consists of a crowd recall module, a crowd category storage system, a crowd classification module, an event message queue, and a voucher. Among them, the event message queue is used to store mass usage. Events such as user clicks, searches, and payments, and send the events of mass users to the crowd classification module; the crowd classification module is used to divide the mass users into several crowd categories based on events in the event message queue, and The classified category is notified to the crowd category storage system; the voucher library is used to store coupons, and the stored coupon information is notified to the crowd category storage system; the crowd category storage system is used to store the correspondence between the crowd category and the coupon; the above processes are all Achieved through offline operations;
When user A accesses, the crowd recall module obtains the crowd category to which user A belongs, and obtains the correspondence relationship between the crowd category and the coupon from the crowd category storage system. According to the crowd category to which user A belongs and the correspondence relationship, A ticket corresponding to the type of crowd to which the user A belongs is determined.
The second link consists of a user's real-time status acquisition module, a tag recall module, a user characteristics storage system, and a coupon storage system. Among them, the coupon storage system is used to store coupons, and the user characteristics storage system is used to store the user's User characteristics; when user A accesses, the user's real-time status acquisition module obtains the real-time status information of user A (for example, the real-time location and the weather corresponding to the location, business opportunities, etc.) and sends it to the tag recall module ; The tag recall module obtains the user characteristic information of the user A from the user characteristic storage system, and combines the real-time status information of the user A and the user characteristic information to form the context information of the user A, and then use the context information The ticket storage system is searched to determine a ticket corresponding to the context information of the user A.
The ranking recommendation module sorts the coupons corresponding to the category of the user to which the user A belongs, as determined by the crowd recall module, and the coupons corresponding to the context information of the user A, which is determined by the recall module, and returns them to the user in order. A.
It can be seen that in the marketing system based on this technical solution, the two links can reuse the sequencing recommendation module.
In the embodiment of the present specification, the integrated recommendation of the real-time crowd and instant status in the marketing system based on this technical solution improves the recommendation method of the coupon in the recommendation marketing, and further improves the recall coupon data related to the user, and then selects the user's feeling Interest coupons, improve the overall recommendation efficiency.
It can be seen from the above embodiment that in this embodiment, a user can be recommended to the user based on the user's status information and user characteristics; at the same time, the user can be recommended to the user based on the category of the user to which the user belongs. , That is, two resource recommendation methods can be supported at the same time. In addition, since the user's status information, user characteristics information, and user category can largely reflect the user's interests and current needs, this manual The embodiment can realize accurate recommendation of resources and improve recommendation efficiency.
FIG. 4 is a schematic structural diagram of a resource recommendation device according to an embodiment of the present specification. As shown in FIG. 4, in a software implementation, the resource recommendation device 400 may include an acquisition unit 401, a determination unit 402, and a recommendation unit 403, where ,
The obtaining unit 401 is configured to obtain status information, user characteristic information, and category information of a target user in a case that a preset resource recommendation condition is satisfied;
A determining unit 402, configured to determine a resource to be recommended matching the target user according to the status information, the user characteristic information, and the crowd category information;
The recommendation unit 403 is configured to recommend the resource to be recommended to the target user.
It can be seen from the above embodiment that in this embodiment, a user can be recommended to a corresponding resource based on the user's status information, user characteristics, and the type of crowd to which the user belongs; due to the user's status information, user characteristics information, and The type of crowd to which a user belongs can largely reflect the user's interests and current needs. Therefore, the embodiments of this specification can achieve accurate recommendation of resources and improve recommendation efficiency.
Optionally, as an embodiment, the determining unit 402 may include:
A first resource determination subunit, configured to determine a first type of resource to be recommended that matches the target user according to the status information and the user characteristic information; and a second resource determination subunit, used to determine Based on the crowd category information, a second type of resources to be recommended that matches the target user is determined.
Optionally, as an embodiment, the first resource determination subunit may include:
A context information generating subunit, configured to generate context information for describing the target user according to the status information and the user characteristic information;
The first type of resource to be recommended determination subunit is configured to retrieve a preset resource base according to the context information, and obtain a first type of resource to be recommended that matches the context information.
Optionally, as an embodiment, the recommendation unit 403 may include:
A first sorting subunit, configured to perform a hybrid sorting on the first-type to-be-recommended resources and the second-type to-be-recommended resources to obtain a hybrid-sorting result;
The first recommendation subunit is configured to recommend the mixed ranking result to the target user.
Optionally, as an embodiment, the recommendation unit 403 may include:
A second sorting subunit for sorting resources in the first type of resources to be recommended to obtain a first ranking result; and a third sorting subunit for sorting resources in the second type of resources to be recommended Perform sorting to obtain a second sorting result;
A second recommendation subunit is configured to recommend the first ranking result and the second ranking result to the target user, respectively.
Optionally, as an embodiment, the resource recommendation device 400 may further include:
A detecting unit, configured to determine that the preset resource recommendation condition is satisfied when an update of the preset resource library is detected; or
The monitoring unit is configured to determine that the preset resource recommendation condition is met when an access event triggered by the target user is monitored.
Optionally, as an embodiment, the status information may include at least one of the following:
The current location of the target user, the environment in which the target user is currently located, an event occurring at the current location of the target user, a location specified in advance by the target user, the target usage The environment in which the user specifies the location in advance and the event occurring in the location specified by the target user in advance.
The resource recommendation device 400 may also execute the method in the embodiment shown in FIG. 1 and implement the functions of the resource recommendation device in the embodiment shown in FIG. 4, which is not described in the embodiment of this specification.
FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present specification. As shown in FIG. 5, at the hardware level, the electronic device includes a processor and optionally an internal bus, a network interface, and a memory. The memory may include a memory, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory, etc. . Of course, the electronic device may also include hardware required for other businesses.
The processor, network interface and memory can be connected to each other through an internal bus. The internal bus can be an ISA (Industry Standard Architecture, Industry Standard Architecture) bus, and a PCI (Peripheral Component Interconnect) bus. Or EISA (Extended Industry Standard Architecture) buses. The bus can be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, only a two-way arrow is used in FIG. 5, but it does not mean that there is only one bus or one type of bus.
Memory for programs. Specifically, the program may include code, and the code includes a computer operation instruction. The memory may include a memory and a non-volatile memory, and provide instructions and data to the processor.
The processor reads the corresponding computer program from the non-volatile memory into the memory and runs it to form a resource recommendation device on a logical level. The processor executes programs stored in the memory and is specifically used to perform the following operations:
When the preset resource recommendation conditions are met, the status information of the target user, user characteristics information, and information about the category of the population to which the user belongs are obtained;
Determining, according to the status information, the user characteristic information, and the crowd category information, a resource to be recommended that matches the target user;
Recommending the resource to be recommended to the target user.
The method performed by the resource recommendation apparatus disclosed in the embodiment shown in FIG. 5 of the present specification may be applied to a processor or implemented by a processor. The processor may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method may be completed by an integrated logic circuit of hardware in a processor or an instruction in a form of software. The above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc .; it may also be a digital signal processor (DSP), a dedicated Integrated Circuit (Application Specific Integrated Circuit, ASIC), Field Programmable Gate Array (FPGA), or other programmable logic device, gate or transistor logic device, gate hardware components. Various methods, steps, and logical block diagrams disclosed in the embodiments of the present specification can be implemented or executed. A general-purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of the method disclosed in combination with the embodiments of the present specification may be directly embodied as being executed by a hardware decoding processor, or may be executed by using a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium such as a random memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically readable and writable programmable memory, a register, and the like. The storage medium is located in the memory, and the processor reads the information in the memory and completes the steps of the above method in combination with its hardware.
The electronic device may also execute the method in FIG. 1 and implement the functions of the resource recommendation device in the embodiment shown in FIG. 1, which is not repeatedly described in the embodiments of this specification.
Of course, in addition to the software implementation, the electronic device in this specification does not exclude other implementations, such as logical devices or a combination of hardware and software. In other words, the execution body of the following processing flow is not limited to each logical unit. , It can also be a hardware or logical device.
An embodiment of the present specification also proposes a computer-readable storage medium that stores one or more programs, the one or more programs include instructions, and the instructions should be portable electronic devices including multiple application programs. When the device is executed, the portable electronic device can be caused to execute the method in the embodiment shown in FIG. 1, and is specifically configured to execute the following method:
When the preset resource recommendation conditions are met, the status information of the target user, user characteristics information, and information about the category of the population to which the user belongs are obtained;
Determining, according to the status information, the user characteristic information, and the crowd category information, a resource to be recommended that matches the target user;
Recommending the resource to be recommended to the target user.
In short, the above descriptions are merely preferred embodiments of the present specification, and are not intended to limit the protection scope of the present specification. Any modification, equivalent replacement, or improvement made within the spirit and principle of this specification shall be included in the protection scope of this specification.
The system, device, module, or unit described in the foregoing embodiments may be specifically implemented by a computer chip or entity, or by a product having a certain function. A typical implementation is a computer. Specifically, the computer may be, for example, a personal computer, a laptop, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, or a wearable device. Or a combination of any of these devices.
Computer-readable media includes permanent and non-permanent, removable and non-removable media. Information can be stored by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), and other types of random access memory (RAM) , Read-only memory (ROM), electrically erasable and programmable read-only memory (EEPROM), flash memory or other memory technologies, read-only disc read-only memory (CD-ROM), digital multifunction Optical discs (DVDs) or other optical storage, magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transmitting media may be used to store information that can be accessed by computing devices. According to the definition in this article, computer-readable media does not include temporary computer-readable media (transitory media), such as modulated data signals and carrier waves.
It should also be noted that the terms "including,""including," or any other variation thereof are intended to encompass non-exclusive inclusion, so that a process, method, product, or device that includes a series of elements includes not only those elements, but also Other elements not explicitly listed, or those that are inherent to such a process, method, product, or device. Without more restrictions, the elements defined by the sentence "including one ..." do not exclude the existence of other identical elements in the process, method, product or equipment including the elements.
Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple. For the relevant part, refer to the description of the method embodiment.
102、104、106、202、204、206、208、2041、2042、2081、2082、2083‧‧‧步驟102, 104, 106, 202, 204, 206, 208, 2041, 2042, 2081, 2082, 2083
400‧‧‧資源推薦裝置 400‧‧‧ resource recommendation device
401‧‧‧獲取單元 401‧‧‧Get Unit
402‧‧‧判定單元 402‧‧‧Judgment unit
403‧‧‧推薦單元 403‧‧‧Recommended Unit
為了更清楚地說明本說明書實施例或現有技術中的技術方案，下面將對實施例或現有技術描述中所需要使用的附圖作簡單地介紹，顯而易見地，下面描述中的附圖僅僅是本說明書中記載的一些實施例，對於本領域普通技術人員來講，在不付出創造性勞動性的前提下，還可以根據這些附圖獲得其他的附圖。In order to more clearly explain the embodiments of the present specification or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only the present invention. For some ordinary people skilled in the art, some embodiments described in the description can also obtain other drawings according to the drawings without paying creative labor.
圖1是本說明書的一個實施例的資源推薦方法的流程圖； FIG. 1 is a flowchart of a resource recommendation method according to an embodiment of the present specification; FIG.
圖2是本說明書的另一個實施例的資源推薦方法的流程圖； 2 is a flowchart of a resource recommendation method according to another embodiment of the present specification;
圖3是本說明書的一個實施例的行銷系統的架構圖； 3 is an architecture diagram of a marketing system according to an embodiment of the present specification;
圖4是本說明書的一個實施例的資源推薦裝置的結構示意圖； 4 is a schematic structural diagram of a resource recommendation device according to an embodiment of the present specification;
圖5是本說明書的一個實施例的電子設備的結構示意圖。 FIG. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present specification.
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Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108563680A (en) * | 2018-03-07 | 2018-09-21 | 阿里巴巴集团控股有限公司 | Resource recommendation method and device |
| CN111125497A (en) * | 2018-10-29 | 2020-05-08 | 北京国双科技有限公司 | Information recommendation method, device, processor and storage medium |
| CN109543132A (en) * | 2018-11-22 | 2019-03-29 | 深圳墨世科技有限公司 | Content recommendation method, device, electronic equipment and storage medium |
| CN109711867B (en) * | 2018-12-07 | 2023-05-30 | 广州市诚毅科技软件开发有限公司 | Shopping image construction marketing method and system based on audience big data |
| CN111292114B (en) * | 2018-12-10 | 2023-06-23 | 百度在线网络技术（北京）有限公司 | Method and device for generating labels |
| CN110659947A (en) * | 2019-10-11 | 2020-01-07 | 沈阳民航东北凯亚有限公司 | Commodity recommendation method and device |
| CN111428134B (en) * | 2020-03-19 | 2023-07-14 | 北京乐蜜科技有限责任公司 | Recommendation information acquisition method and device, electronic equipment and storage medium |
| CN111985765B (en) * | 2020-07-06 | 2024-04-05 | 招联消费金融股份有限公司 | Method, device, equipment and storage medium for determining resource provider |
| CN112767049A (en) * | 2021-01-27 | 2021-05-07 | 支付宝(杭州)信息技术有限公司 | Target object processing method and device |
| CN113609266B (en) * | 2021-07-09 | 2024-07-16 | 阿里巴巴创新公司 | Resource processing method and device |
Family Cites Families (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2015012574A (en) * | 2013-07-02 | 2015-01-19 | 日本電信電話株式会社 | Video content recommend device, method and program |
| CN103714139B (en) * | 2013-12-20 | 2017-02-08 | 华南理工大学 | Parallel data mining method for identifying a mass of mobile client bases |
| CN105488689A (en) * | 2015-11-19 | 2016-04-13 | 北京百度网讯科技有限公司 | Real-time recommendation method and device of consumption information |
| CN107545444B (en) * | 2016-06-23 | 2021-03-16 | 腾讯科技（深圳）有限公司 | Business advertisement data recommendation method and device |
| CN106850857B (en) * | 2017-03-28 | 2020-02-07 | 广州心源互动科技有限公司 | Personalized service pushing method and system based on user information |
| CN107341173B (en) * | 2017-05-16 | 2021-01-05 | 创新先进技术有限公司 | Information processing method and device |
| CN107222557A (en) * | 2017-06-27 | 2017-09-29 | 乐视致新电子科技（天津）有限公司 | Information recommendation method, device and server |
| CN108563680A (en) * | 2018-03-07 | 2018-09-21 | 阿里巴巴集团控股有限公司 | Resource recommendation method and device |
-
2018
- 2018-03-07 CN CN201810185111.2A patent/CN108563680A/en active Pending
- 2018-12-26 TW TW107147127A patent/TW201939378A/en unknown
-
2019
- 2019-01-28 WO PCT/CN2019/073383 patent/WO2019169978A1/en active Application Filing
Also Published As
| Publication number | Publication date |
|---|---|
| CN108563680A (en) | 2018-09-21 |
| WO2019169978A1 (en) | 2019-09-12 |
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