WO2017101407A1 - 视频推荐方法、系统及服务器 - Google Patents
视频推荐方法、系统及服务器 Download PDFInfo
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- WO2017101407A1 WO2017101407A1 PCT/CN2016/089524 CN2016089524W WO2017101407A1 WO 2017101407 A1 WO2017101407 A1 WO 2017101407A1 CN 2016089524 W CN2016089524 W CN 2016089524W WO 2017101407 A1 WO2017101407 A1 WO 2017101407A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
- H04N21/25866—Management of end-user data
- H04N21/25891—Management of end-user data being end-user preferences
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/45—Management operations performed by the client for facilitating the reception of or the interaction with the content or administrating data related to the end-user or to the client device itself, e.g. learning user preferences for recommending movies, resolving scheduling conflicts
- H04N21/466—Learning process for intelligent management, e.g. learning user preferences for recommending movies
- H04N21/4668—Learning process for intelligent management, e.g. learning user preferences for recommending movies for recommending content, e.g. movies
Definitions
- the present application relates to the field of network video, and in particular, to a video recommendation method, system, and server.
- the server can push the popular video to the client to attract the user to click or view, but in the prior art, the popular video pushed is recommended according to the number of views of the video, so that the new online
- the chances of a video getting recommended are smaller, and it also causes some videos to accumulate a large amount of views due to their time of existence, but since the ratio of their views to their time of existence is already small, you may not have the video.
- Interested in resulting in reduced user experience with recommended videos. Therefore, it is necessary to provide a new scheme to achieve the accuracy of video recommendation, and to recommend hotspot videos to users according to more factors, thereby making the video recommendation scheme more reasonable and improving the user experience.
- An object of the embodiments of the present invention is to provide a video recommendation method, system, and server to recommend a hotspot video to a user in different manners to improve the user experience.
- an embodiment of the present invention provides a video recommendation method, which includes: acquiring attributes of hot words and hot words provided by a search engine; sorting hot words according to attributes of the hot words; Hot word recommendation video.
- the method further includes: performing a deduplication operation on the obtained hot word; Sorting the hot words by the attributes of the hot words includes: sorting the hot words after the deduplication operation according to the attributes of the hot words obtained by the deduplication operation; the recommended videos according to the sorted hot words include: according to the sorted The hot word recommendation video after the heavy operation.
- the performing the deduplication operation on the obtained hot words comprises: performing a word segmentation operation on the obtained hot words and obtaining a word segment set corresponding to the hot words; determining an overlap degree between the respective word segment sets; When the degree of overlap of the word segmentation reaches the threshold, the shorter term hot words of the two hot words corresponding to the two word segment sets are selected, and another hot word is deleted.
- the attributes of the hot word include the ranking of the hot words and the time at which the hot words appear.
- the sorting the hot words according to the attributes of the hot words includes: determining a trend evaluation value of the hot words, a time evaluation value of the hot words, and a ranking evaluation value of the hot words At least one of the hot words is sorted according to at least one of a trend evaluation value of the hot word, a time evaluation value of the hot word, and a ranking evaluation value of the hot word.
- the trend value of the hot word, the time evaluation value of the hot word, and the heat are higher in the end time of the hot word in the predetermined start time to the end time. The higher of at least one of the word's ranking evaluation values.
- an embodiment of the present invention provides a server, where the server includes: an obtaining module, configured to acquire attributes of a hot word and a hot word provided by a search engine; and a sorting module, configured to use the hot word according to the attribute of the hot word Sorting; a recommendation module for recommending videos based on the sorted hot words.
- the obtaining module is further configured to perform a deduplication operation on the obtained hot words;
- the sorting module is further configured to sort the hot words after the deduplication according to the attributes of the hot words obtained by the deduplication operation.
- the recommendation module is further configured to recommend a video according to the hot words after the sorted deduplication operation.
- the obtaining module is further configured to perform a word segmentation operation on the obtained hot words and obtain a word segment set corresponding to the hot words; determine an overlap degree between the respective word segment sets; and achieve overlap in the two word segment sets In the case of a threshold, select the length of the two hot words corresponding to the two word segment sets Shorter hot words and delete another hot word.
- the attributes of the hot word include the ranking of the hot words and the time at which the hot words appear.
- the ranking module is further configured to determine at least one of a trend evaluation value of the hot word, a time evaluation value of the hot word, and a ranking evaluation value of the hot word; At least one of the trend evaluation value of the hot word, the time evaluation value of the hot word, and the ranking evaluation value of the hot word sorts the hot words.
- the trend value of the hot word, the time evaluation value of the hot word, and the heat are higher in the end time of the hot word in the predetermined start time to the end time. The higher of at least one of the word's ranking evaluation values.
- the embodiment of the present invention provides a video recommendation system, which includes the server and the client according to any one of claims 7-12; and the client is configured to display the video recommended by the server.
- the video is recommended by considering factors such as the ranking of the hot words of the video and the time when the hot words appear, so that the recommended video can conform to the current hotspot and can improve the user experience.
- FIG. 1 is a schematic diagram of a video recommendation method according to an embodiment of the present invention.
- FIG. 2 is a flowchart of a deduplication operation according to an embodiment of the present invention.
- FIG. 3 is a schematic diagram of a server according to an embodiment of the present invention.
- FIG. 4 is a schematic diagram of a video recommendation system according to an embodiment of the present invention.
- the embodiment of the present invention provides the following embodiments.
- the method specifically includes: acquiring attributes of a hot word and a hot word provided by a search engine (step 101); The attributes of the words sort the hot words (step 103); the video is recommended based on the sorted hot words (step 105).
- some search engines provide hot word lists, such as Baidu, etc.
- the present invention can automatically crawl the hot words and hot words in the hot word list through the crawler protocol, so that hot words can be used to recommend videos.
- the attributes of the hot words may include the ranking of the hot words, the time when the hot words appear, and the like.
- hot words such as manually viewing the top 50 of the hot word list, and recording the time when hot words and hot words appear.
- a hot lexicon can be formed by continuous crawling or recording, such as crawling or recording once a day. It is possible to preset a hot word that retains only a predetermined period of time, for example, crawling or recording once a day to form a hot vocabulary for three consecutive days. Hot words that are more than aging can be deleted, or not considered in the case of reservations, that is, when hot words are sorted, hot words that are more than time-sensitive, such as hot words three days ago, are not considered.
- the deduplication operation can use the technical solutions existing in the prior art.
- the deduplication operation may be performed by using the solution shown in FIG. 2, specifically: performing a word segmentation operation on the obtained hot words and obtaining a word segment set corresponding to the hot words (step 201); determining each word segment set Inter-level overlap (step 203); determining whether the overlap degree of the two word segment sets reaches a threshold value (step 205), and if the threshold value is reached, selecting the short-term hot words of the two hot words corresponding to the two word segment sets, And deleting another hot word (step 207), further determining whether the comparison between the overlap degree between the two sets and the threshold is completed (step 209), that is, determining whether the deduplication operation ends, and if the hot word deduplication operation ends, Then the whole process is ended, otherwise step 203 is continued.
- step 205 If it is determined in step 205 that the degree of overlap does not exceed the threshold, then the overlap degree comparison between the word segment sets is continued, and step 203 is performed.
- the deduplication process it is necessary to traverse whether the overlap between any two participles reaches a threshold.
- the threshold When the threshold is reached, the shorter one of the corresponding hot words is selected, and the other is deleted, so that the required amount of calculation can be reduced.
- the degree of overlap may be determined according to the number of identical participles in each set, for example, the number of the same part of the two participle sets may be divided by the number of participles in the set of words with the least participle, and if 80% is reached, the two participles may be considered The overlap of the sets reaches the threshold. For example, by comparing the hot words "Apple Publishing Conference” and "Apple Publishing Conference 2015", the two can be regarded as repeated hot words, and the "Apple Publishing Conference 2015” is deleted and the processed hot word "Apple Publishing Conference” is obtained.
- the hot words can be sorted by the deduplication operation and the video is further recommended according to the hot words after the sorted deduplication operation.
- hot word attributes such as the ranking of hot words and the time when hot words appear can be used.
- the hot word attributes used in the embodiments of the present invention are not limited thereto, and only two examples will be described herein.
- At least one of the trend evaluation value, the time evaluation value of the hot word, and the ranking evaluation value of the hot word may be determined in the sorting process.
- the trend evaluation value, the time evaluation value of the hot word, and the ranking evaluation value of the hot word can be determined simultaneously. Specifically, at the scheduled At least one of the trend evaluation value of the hot word, the time evaluation value of the hot word, and the ranking evaluation value of the hot word in the start time to the end time, the higher the hot word is ranked in the end time The higher the person.
- the trend evaluation value can be determined by the change of the hot word ranking in the past 3 days, for example, the ranking is set to 3 points, and the ranking is unchanged.
- the ranking drop is set to 1 point;
- the time evaluation value can be set by the following method, if the hot word is ranked on the last day, it gives 3 points, the hot word is ranked on the first day, and the hot word is ranked first. On the second day, give 2 points; the hot word ranking evaluation value can be the current ranking related score, the higher the current ranking, the higher the score, for example, the statistics of 50 hot words, you can subtract the hot words by 51
- the current ranking is used to calculate the hot word ranking, so that it can reflect the ranking of the hot word.
- the popular video can be ranked, and Recommend to users to improve the user experience of watching videos.
- the embodiment of the present invention provides a server.
- the server includes: an obtaining module 100, configured to acquire attributes of hot words and hot words provided by a search engine; and a sorting module 200, configured to The attribute of the hot word sorts the hot words; the recommendation module 300 is used to recommend the video according to the sorted hot words.
- the obtaining module 100 also performs a deduplication operation on the hot words, so that the sorting module 200 can perform sorting using the hot words after the deduplication operation, and the recommendation module can perform the recommended video according to the hot words of the deduplication operation.
- the embodiment of the present invention provides a video recommendation system diagram, as shown in FIG. 4, including a server 400 and a client 500.
- the client is mainly used to display a video recommended by the server.
Abstract
本发明实施例涉及网络视频领域，公开了一种视频推荐方法、系统及服务器。该方法包括：获取搜索引擎提供的热词及热词的属性；根据所述热词的属性对热词进行排序；根据排序后的热词推荐视频。本发明实施例通过考虑视频热词的排名、热词出现的时间等因素综合考虑来推荐视频，从而使得推荐的视频更能够符合当前热点，并能够提升用户的体验。
Description
本申请要求在2015年12月14日提交中国专利局、申请号为201510923442.8的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
本申请涉及网络视频领域，具体地，涉及一种视频推荐方法、系统及服务器。
现有技术中，对于视频内容，服务器可以向客户端推送热门的视频以吸引用户点击或观看，但是现有技术中，所推送的热门视频是根据视频的观看数量进行推荐，从而使得新上线的视频得到推荐的几率变小，并且也会使得一些视频由于其存在的时间就而累积了大量的观看数量，但是由于其观看数量相对于其存在时间的比值已经很小，大家可能已经不对该视频感兴趣，导致用户对推荐视频的体验降低。因此，有必要提供新的方案来实现视频推荐的准确性，并能够依据更多的因素来向用户推荐热点视频，从而使得视频推荐方案更合理，提高用户的体验。
发明内容
本发明实施例的目的是提供一种视频推荐方法、系统及服务器，以通过不同的方式来向用户推荐热点视频，提高用户的体验。
为了实现上述目的，本发明实施例提供了一种视频推荐方法，该方法包括：获取搜索引擎提供的热词及热词的属性；根据所述热词的属性对热词进行排序；根据排序后的热词推荐视频。
在一个实施例中，还包括：对获取的热词进行去重操作；则，所述根据
所述热词的属性对热词进行排序包括：根据去重操作得到的热词的属性对去重操作后的热词进行排序；所述根据排序后的热词推荐视频包括：根据排序后的去重操作后的热词推荐视频。
在一个实施例中，所述对获取的热词进行去重操作包括：对获取的热词进行分词操作并得到与热词对应的分词集合；确定各个分词集合之间的重叠度；在两个分词集合的重叠度达到阈值的情况下，选取该两个分词集合对应的两个热词中长度较短的热词，并删除另一热词。
在一个实施例中，所述热词的属性包括热词的排名以及热词出现的时间。
在一个实施例中，所述根据所述热词的属性对热词进行排序包括：确定所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者；根据所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者对热词进行排序。
在一个实施例中，在预定的开始时间至结束时间内，所述热词在结束时间排名越靠前则所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者越高。
相应地，本发明实施例提供了一种服务器，该服务器包括：获取模块，用于获取搜索引擎提供的热词及热词的属性；排序模块，用于根据所述热词的属性对热词进行排序；推荐模块，用于根据排序后的热词推荐视频。
在一个实施例中，所述获取模块还用于对获取的热词进行去重操作；所述排序模块还用于根据去重操作得到的热词的属性对去重操作后的热词进行排序；所述推荐模块还用于根据排序后的去重操作后的热词推荐视频。
在一个实施例中，所述获取模块还用于对获取的热词进行分词操作并得到与热词对应的分词集合；确定各个分词集合之间的重叠度；在两个分词集合的重叠度达到阈值的情况下，选取该两个分词集合对应的两个热词中长度
较短的热词，并删除另一热词。
在一个实施例中，所述热词的属性包括热词的排名以及热词出现的时间。
在一个实施例中，所述排序模块还用于确定所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者；根据所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者对热词进行排序。
在一个实施例中，在预定的开始时间至结束时间内，所述热词在结束时间排名越靠前则所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者越高。
本发明实施例提供了一种视频推荐系统，该系统包括根据权利要求7-12任意一项所述的服务器以及客户端；所述客户端用于显示所述服务器推荐的视频。
本发明实施例通过考虑视频热词的排名、热词出现的时间等因素综合考虑来推荐视频，从而使得推荐的视频更能够符合当前热点，并能够提升用户的体验。
本发明实施例的其它特征和优点将在随后的具体实施方式部分予以详细说明。
附图是用来提供对本发明实施例的进一步理解，并且构成说明书的一部分，与下面的具体实施方式一起用于解释本发明，但并不构成对本发明的限制。在附图中：
图1是本发明实施例提供的视频推荐方法示意图；
图2是本发明实施例提供的去重操作流程图；
图3是本发明实施例提供的服务器示意图；
图4是本发明实施例提供的视频推荐系统示意图。
附图标记说明
100 获取模块 200 排序模块
300 推荐模块 500 服务器
600 客户端
以下结合附图对本发明的具体实施方式进行详细说明。应当理解的是，此处所描述的具体实施方式仅用于说明和解释本发明，并不用于限制本发明。
为了更准确地向用户推荐视频，本发明实施例提供了如下的实施方式，如图1所示，具体包括：获取搜索引擎提供的热词及热词的属性(步骤101)；根据所述热词的属性对热词进行排序(步骤103)；根据排序后的热词推荐视频(步骤105)。目前有些搜索引擎会提供热词榜，例如百度等，本发明可以通过爬虫协议自动爬取热词榜中的热词以及热词的属性，从而可以利用热词来推荐视频。热词的属性可以包括热词的排名、热词出现的时间等。作为替代，也可以人工获取热词，例如人工查看热词榜的前50名，记录热词及热词出现的时间。通过连续的爬取或记录，例如每天爬取或记录一次，可以形成热词库。可以预先设定只保留预定时间段的热词，例如每天爬取或记录一次，形成连续3天的热词库。超过时效的热词可以删除，或者在保留的情况下不予考虑，即在对热词进行排序时不考虑超过时效的热词，例如三天前的热词。
为了精简热词，需要对热词进行去重操作。去重操作可以使用现有技术中存在的技术方案。本发明实施例中，可以通过如图2所示的方案进行去重操作，具体包括：对获取的热词进行分词操作并得到与热词对应的分词集合(步骤201)；确定各个分词集合之间的重叠度(步骤203)；判断两个分词集合的重叠度是否达到阈值(步骤205)，如果达到阈值，则选取该两个分词集合对应的两个热词中长度较短的热词，并删除另一热词(步骤207)，进一步判断任意两个集合之间重叠度与阈值之间的比较是否完成(步骤209)，即判断去重操作是否结束，如果热词去重操作结束，则结束整个流程，否则继续执行步骤203。如步骤205确定重叠度没有超过阈值，则继续执行分词集合之间的重叠度比较，执行步骤203。在去重过程中，需要遍历任意两个分词之间的重叠度是否达到阈值，达到阈值则选取对应的热词中较短的一个，并删除另一个，这样可以减少所需的运算量。重叠度可以根据各个集合中相同分词的数量来确定，例如可以根据两个分词集合中相同的分词数量除以具有最少分词的分词集合中的分词数量，如果达到80％则可以认为该两个分词集合的重叠度达到阈值。例如通过比较热词“苹果发布会”和“苹果发布会2015”，可将二者认为是重复的热词，并将“苹果发布会2015”删除而得到处理后的热词“苹果发布会”。
在进行去重操作以后，可以通过去重操作后的热词排序并进一步地根据排序后的去重操作后的热词推荐视频。
在对热词进行排序的过程中，可以使用例如热词的排名以及热词出现的时间之类的热词属性。本发明实施例所使用的热词属性不限于此，在此仅以二者为例进行说明。
在排序的过程可以确定趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者。一个例子是，可以同时确定趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值。具体而言，在预定的
开始时间至结束时间内，所述热词在结束时间排名越靠前则所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者越高。例如，在使用最近三天的热词进行视频推荐的情况下，趋势评估值可以通过过去3天热词名次的变化来确定该趋势评估值，例如排名上升则设置为3分，排名不变设置为2分，排名下降设置为1分；时间评估值可以通过以下方式设置，如果热词最高排名在最后一天则给3分，热词最高排名在第一天则给1分，热词最高排名在第2天则给2分；热词排名评估值可以是当前排名相关的分数，当前排名越靠前，则分数越高，例如对50个热词进行统计，可以通过51减去热词的当前排名来计算该热词排民分，从而能反映出该热词的排名情况。
通过将上述分词通过运算符进行计算，例如将上述参数相乘，或者将前三个参数相乘，并计算与后两个参数乘积相加作为排名的依据，从而可以对热门视频进行排名，并向用户进行推荐，以提高用户观看视频的体验。
相应地，本发明实施例提供了一种服务器，如图3所示，该服务器包括：获取模块100，用于获取搜索引擎提供的热词及热词的属性；排序模块200，用于根据所述热词的属性对热词进行排序；推荐模块300，用于根据排序后的热词推荐视频。一个例子是，获取模块100还对热词进行去重操作，从而排序模块200可以利用去重操作后的热词进行排序，而推荐模块可以根据去重操作的热词进行推荐视频。
相应地，本发明实施例提供了一种视频推荐系统图，如图4所示，包括服务器400以及客户端500，客户端主要用于显示服务器推荐的视频。
以上结合附图详细描述了本发明的优选实施方式，但是，本发明实施例并不限于上述实施方式中的具体细节，在本发明的技术构思范围内，可以对本发明的技术方案进行多种简单变型，这些简单变型均属于本发明的保护范围。
另外需要说明的是，在上述具体实施方式中所描述的各个具体技术特征，在不矛盾的情况下，可以通过任何合适的方式进行组合。为了避免不必要的重复，本发明对各种可能的组合方式不再另行说明。
此外，本发明的各种不同的实施方式之间也可以进行任意组合，只要其不违背本发明的思想，其同样应当视为本发明所公开的内容。
Claims (13)
- 一种视频推荐方法，包括：获取搜索引擎提供的热词及热词的属性；根据所述热词的属性对热词进行排序；根据排序后的热词推荐视频。
- 根据权利要求1所述的视频推荐方法，其中，还包括：对获取的热词进行去重操作；则，所述根据所述热词的属性对热词进行排序包括：根据去重操作得到的热词的属性对去重操作后的热词进行排序；所述根据排序后的热词推荐视频包括：根据排序后的去重操作后的热词推荐视频。
- 根据权利要求2所述的视频推荐方法，其中，所述对获取的热词进行去重操作包括：对获取的热词进行分词操作并得到与热词对应的分词集合；确定各个分词集合之间的重叠度；在两个分词集合的重叠度达到阈值的情况下，选取该两个分词集合对应的两个热词中长度较短的热词，并删除另一热词。
- 根据权利要求1-3中任意一项所述的视频推荐方法，其中，所述热词的属性包括热词的排名以及热词出现的时间。
- 根据权利要求4所述的视频推荐方法，其中，所述根据所述热词的属性对热词进行排序包括：确定所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的 排名评估值中的至少一者；根据所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者对热词进行排序。
- 根据权利要求5所述的视频推荐方法，其中，在预定的开始时间至结束时间内，所述热词在结束时间排名越靠前则所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者越高。
- 一种服务器，包括：获取模块，用于获取搜索引擎提供的热词及热词的属性；排序模块，用于根据所述热词的属性对热词进行排序；推荐模块，用于根据排序后的热词推荐视频。
- 根据权利要求7所述的服务器，其中，所述获取模块还用于对获取的热词进行去重操作；所述排序模块还用于根据去重操作得到的热词的属性对去重操作后的热词进行排序；所述推荐模块还用于根据排序后的去重操作后的热词推荐视频。
- 根据权利要求8所述的服务器，其中，所述获取模块还用于对获取的热词进行分词操作并得到与热词对应的分词集合；确定各个分词集合之间的重叠度；在两个分词集合的重叠度达到阈值的情况下，选取该两个分词集合对应的两个热词中长度较短的热词，并删除另一热词。
- 根据权利要求7-9中任意一项所述的服务器，其中，所述热词的属性包括热词的排名以及热词出现的时间。
- 根据权利要求10所述的服务器，其中，所述排序模块还用于确定所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者；根据所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者对热词进行排序。
- 根据权利要求11所述的服务器，其中，在预定的开始时间至结束时间内，所述热词在结束时间排名越靠前则所述热词的趋势评估值、所述热词的时间评估值、以及所述热词的排名评估值中的至少一者越高。
- 一种视频推荐系统，该系统包括根据权利要求7-12中任意一项所述的服务器以及客户端；所述客户端用于显示所述服务器推荐的视频。
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