-
公开(公告)号：US08682839B2
公开(公告)日：2014-03-25
申请号：US12131125
申请日：2008-06-02
申请人： Hua Li , Zheng Chen , Jian Wang
发明人： Hua Li , Zheng Chen , Jian Wang
CPC分类号： G06Q30/08 , G06Q30/02 , G06Q30/0256 , G06Q30/0267
摘要： Embodiments of the claimed subject matter provide a method and system for predicting bidding keyword monetization. The claimed subject matter provides a method and system with which the value of a keyword for the purpose of relevant online advertisement may be evaluated according to various metrics to determine a bidding landscape for use in advertising campaigns. The value of the keyword considers certain attributes related to the monetization of the keyword.One embodiment of the claimed subject matter is implemented as a method for predicting keyword monetization for one or more keyword-advertisement relationships. Historical data for the one or more keyword-advertisement relationships is referenced and used to generate a global model of the one or more keyword-advertisement relationship. The relationships are then evaluated according to a time-series analysis, which parses the data from the historical data and the global model to create predictions for the keyword monetization according to the keyword-advertisement relationships.
摘要翻译： 所要求保护的主题的实施例提供了用于预测投标关键字货币化的方法和系统。 所要求保护的主题提供了一种方法和系统，其中可以根据各种度量来评估用于相关在线广告的关键字的价值，以确定用于广告活动的投标景观。 该关键字的值考虑与关键字获利相关的特定属性。 所要求保护的主题的一个实施例被实现为用于预测一个或多个关键字 - 广告关系的关键字获利的方法。 引用一个或多个关键字 - 广告关系的历史数据，并用于生成一个或多个关键字 - 广告关系的全局模型。 然后根据时间序列分析来评估关系，该时间序列分析从历史数据和全球模型中分析数据，以根据关键字 - 广告关系创建关键字营利的预测。
-
公开(公告)号：US07761287B2
公开(公告)日：2010-07-20
申请号：US11552057
申请日：2006-10-23
发明人： Hua Li , Jian-Lai Zhou , Zheng Chen , Jian Wang
CPC分类号： G06F17/2715 , G06Q30/02 , G06Q30/0217 , G06Q30/0282
摘要： An opinion system infers the opinion of a sentence of a product review based on a probability that the sentence contains certain sequences of parts of speech that are commonly used to express an opinion as indicated by the training data and the probabilities of the training data. When provided with the sentence, the opinion system identifies possible sequences of parts of speech of the sentence that are commonly used to express an opinion and the probability that the sequence is the correct sequence for the sentence. For each sequence, the opinion system then retrieves a probability derived from the training data that the sequence contains an opinion word that expresses an opinion. The opinion system then retrieves a probability from the training data that the opinion words of the sentence are used to express an opinion. The opinion system then combines the probabilities to generate an overall probability that the sentence with that sequence expresses an opinion.
摘要翻译： 意见系统根据该训练数据和训练数据概率所指示的句子包含通常用于表达意见的特定词汇序列的概率来推断产品评论句子的意见。 当提供句子时，意见系统识别通常用于表达意见的句子的部分语音的可能序列以及序列是句子的正确序列的概率。 对于每个序列，意见系统然后检索从训练数据得出的概率，该序列包含表达意见的意见词。 然后，意见系统从训练数据中检索出用于表达意见的句子意见词的概率。 然后，意见系统将概率组合以产生具有该序列的句子表达意见的总体概率。
-
公开(公告)号：US20090299831A1
公开(公告)日：2009-12-03
申请号：US12131124
申请日：2008-06-02
申请人： Hua Li , Zheng Chen , Jian Wang
发明人： Hua Li , Zheng Chen , Jian Wang
IPC分类号： G06Q90/00
CPC分类号： G06Q30/02 , G06Q10/025 , G06Q30/0207 , G06Q30/0277 , G06Q40/08
摘要： Embodiments of the claimed subject matter provide a method and system for modeling advertiser monetization. The claimed subject matter provides a method and system from which an advertisement may be evaluated according to various metrics to determine a quality relative to other advertisements. The relative quality considers the content of the advertisement, the performance of the advertisement and the history of the advertiser's bidding behavior.One embodiment of the claimed subject matter is implemented as a method for advertiser monetization modeling. One or more advertisements are received from one or more advertisers. The quality of the advertisement(s) is defined according to certain metrics, such as the quality of the content of the advertisement, the quality of the past and estimated future performance of the advertisement and the history of bidding behavior of the advertiser. After the respective quality of the advertisement(s) is determined, the advertisement(s) is ranked with other advertisements according to the determined quality.
摘要翻译： 所要求保护的主题的实施例提供了用于对广告商获利进行建模的方法和系统。 所要求保护的主题提供了一种方法和系统，从该方法和系统可以根据各种度量来评估广告以确定相对于其他广告的质量。 相对质量考虑广告的内容，广告的表现以及广告商的投标行为的历史。 所要求保护的主题的一个实施例被实现为广告商获利建模的方法。 从一个或多个广告商接收一个或多个广告。 广告的质量根据广告内容的质量，过去的质量以及广告的未来预测表现以及广告主的投标行为的历史等某些指标来定义。 在确定了广告的相应质量之后，根据所确定的质量对广告进行其他广告的排序。
-
公开(公告)号：US20080301117A1
公开(公告)日：2008-12-04
申请号：US11756740
申请日：2007-06-01
申请人： Hua-Jun Zeng , Hua Li , Jian Hu , Han Peng , Zheng Chen , Jian Wang
发明人： Hua-Jun Zeng , Hua Li , Jian Hu , Han Peng , Zheng Chen , Jian Wang
CPC分类号： G06F17/30864 , Y10S707/99935
摘要： A method and system for assessing keyword usage based on frequency of usage of the keywords during various periods is provided. A keyword usage measurement system is provided with the frequency of keywords during various periods. The measurement system then calculates a recent usage score for a keyword by combining a frequency impulse score for the keyword with a frequency weight for the keyword. The frequency impulse score for a keyword indicates whether a recent change in the frequency of the keyword has occurred. The frequency weight for a keyword indicates a recent measure of the frequency of the keyword.
摘要翻译： 提供了一种基于各种期间关键词使用频率来评估关键字使用的方法和系统。 关键字使用测量系统在不同时期提供关键字的频率。 然后，测量系统通过将关键字的频率脉冲得分与该关键字的频率权重组合来计算关键字的最近使用分数。 关键字的频率脉冲得分指示是否发生了关键字的频率的最近的改变。 关键字的频率权重表示最近对关键字频率的度量。
-
公开(公告)号：US20080103886A1
公开(公告)日：2008-05-01
申请号：US11553897
申请日：2006-10-27
申请人： Hua Li , Zheng Chen , Benyu Zhang , Hua-Jun Zeng , Jian Wang
发明人： Hua Li , Zheng Chen , Benyu Zhang , Hua-Jun Zeng , Jian Wang
IPC分类号： G06Q30/00
CPC分类号： G06Q30/02 , G06Q30/0275 , G06Q30/0277
摘要： A method and system for generating and using a combined model to identify whether a bid term is relevant to an advertisement is provided. A relevance system trains a combined model that includes an initial model and a decision tree model that are trained using features that represent relationships between bid terms and advertisements. The relevance system trains the initial model to map initial model features to a modeled relevance. The relevance system trains the decision tree model to map the decision tree features and the modeled relevance to a final relevance. The trained initial model and decision tree model represent the combined model. The relevance system then uses the combined model to determine the relevance of bid terms to advertisements.
摘要翻译： 提供了一种用于生成和使用组合模型以识别出价项是否与广告相关的方法和系统。 相关系统训练包括初始模型和决策树模型的组合模型，该模型使用表示投标条款和广告之间关系的特征来训练。 相关系统训练初始模型以将初始模型特征映射到建模相关性。 相关系统训练决策树模型，将决策树特征和建模相关性映射到最终相关性。 训练初始模型和决策树模型代表组合模型。 相关系统然后使用组合模型来确定投标条款与广告的相关性。
-
公开(公告)号：US20080097758A1
公开(公告)日：2008-04-24
申请号：US11552057
申请日：2006-10-23
申请人： Hua Li , Jian-Lai Zhou , Zheng Chen , Jian Wang , Dongmei Zhang
发明人： Hua Li , Jian-Lai Zhou , Zheng Chen , Jian Wang , Dongmei Zhang
IPC分类号： G10L15/00
CPC分类号： G06F17/2715 , G06Q30/02 , G06Q30/0217 , G06Q30/0282
摘要： An opinion system infers the opinion of a sentence of a product review based on a probability that the sentence contains certain sequences of parts of speech that are commonly used to express an opinion as indicated by the training data and the probabilities of the training data. When provided with the sentence, the opinion system identifies possible sequences of parts of speech of the sentence that are commonly used to express an opinion and the probability that the sequence is the correct sequence for the sentence. For each sequence, the opinion system then retrieves a probability derived from the training data that the sequence contains an opinion word that expresses an opinion. The opinion system then retrieves a probability from the training data that the opinion words of the sentence are used to express an opinion. The opinion system then combines the probabilities to generate an overall probability that the sentence with that sequence expresses an opinion.
摘要翻译： 意见系统根据该训练数据和训练数据概率所指示的句子包含通常用于表达意见的特定词汇序列的概率来推断产品评论的句子的意见。 当提供句子时，意见系统识别通常用于表达意见的句子的部分语音的可能序列以及序列是句子的正确序列的概率。 对于每个序列，意见系统然后检索从训练数据得出的概率，该序列包含表达意见的意见词。 然后，意见系统从训练数据中检索出用于表达意见的句子意见词的概率。 然后，意见系统将概率组合以产生具有该序列的句子表达意见的总体概率。
-
公开(公告)号：US08117050B2
公开(公告)日：2012-02-14
申请号：US12131124
申请日：2008-06-02
申请人： Hua Li , Zheng Chen , Jian Wang
发明人： Hua Li , Zheng Chen , Jian Wang
CPC分类号： G06Q30/02 , G06Q10/025 , G06Q30/0207 , G06Q30/0277 , G06Q40/08
摘要： Embodiments of the claimed subject matter provide a method and system for modeling advertiser monetization. The claimed subject matter provides a method and system from which an advertisement may be evaluated according to various metrics to determine a quality relative to other advertisements. The relative quality considers the content of the advertisement, the performance of the advertisement and the history of the advertiser's bidding behavior.One embodiment of the claimed subject matter is implemented as a method for advertiser monetization modeling. One or more advertisements are received from one or more advertisers. The quality of the advertisement(s) is defined according to certain metrics, such as the quality of the content of the advertisement, the quality of the past and estimated future performance of the advertisement and the history of bidding behavior of the advertiser. After the respective quality of the advertisement(s) is determined, the advertisement(s) is ranked with other advertisements according to the determined quality.
摘要翻译： 所要求保护的主题的实施例提供了用于对广告商获利进行建模的方法和系统。 所要求保护的主题提供了一种方法和系统，从该方法和系统可以根据各种度量来评估广告以确定相对于其他广告的质量。 相对质量考虑广告的内容，广告的表现以及广告商的投标行为的历史。 所要求保护的主题的一个实施例被实现为广告商获利建模的方法。 从一个或多个广告商接收一个或多个广告。 广告的质量根据广告内容的质量，过去的质量以及广告的未来预测以及广告主的投标行为的历史等某些指标来定义。 在确定了广告的相应质量之后，根据所确定的质量对广告进行其他广告的排序。
-
公开(公告)号：US07848918B2
公开(公告)日：2010-12-07
申请号：US11538770
申请日：2006-10-04
申请人： Hua Li , Song Huang , Zheng Chen , Jian Wang
发明人： Hua Li , Song Huang , Zheng Chen , Jian Wang
CPC分类号： G06F17/28
摘要： A method and system for identifying expansions of abbreviations using learned weights is provided. An abbreviation system generates features for various expansions of an abbreviation and generates a score indicating the likelihood that an expansion is a correct expansion of the abbreviation. A expansion with the same number of words as letters in the abbreviation is more likely in general to be a correct expansion than an expansion with more or fewer words. The abbreviation system calculates a score based on a weighted combination of the features. The abbreviation system learns the weights for the features from training data of abbreviations, candidate expansions, and scores for the candidate expansions.
摘要翻译： 提供了一种用于使用学习的权重来识别缩写的扩展的方法和系统。 缩写系统产生缩写的各种扩展的特征，并生成表示扩展是缩写的正确扩展的可能性的分数。 与缩写中的字母相同数量的单词的扩展通常可能是具有更多或更少单词的扩展的正确扩展。 缩写系统基于特征的加权组合来计算得分。 缩写系统从候选扩展的缩写，候选扩展和分数的训练数据中学习特征的权重。
-
9.发明申请公开(公告)号：US20080313180A1
公开(公告)日：2008-12-18
申请号：US11763282
申请日：2007-06-14
申请人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Duo Zhang , Jian Wang
发明人： Hua-Jun Zeng , Hua Li , Jian Hu , Zheng Chen , Duo Zhang , Jian Wang
IPC分类号： G06F17/30
CPC分类号： G06F17/30731 , G06Q30/02
摘要： A topic identification system identifies topics of online discussions by iteratively identifying topic words or keywords of the online discussions and identifying language patterns associated with those keywords. The topic identification system starts out with an initial set of keywords and identifies language patterns that each include a keyword. The topic identification system then uses the identified language patterns to identify additional keywords of the online discussion that match the patterns. The topic identification system then again identifies language patterns using the keywords including the newly identified keywords. The topic identification system may repeat the process of identifying language patterns and keywords until a termination criterion is satisfied.
摘要翻译： 主题识别系统通过迭代地识别在线讨论的主题或关键字并识别与这些关键字相关联的语言模式来识别在线讨论的主题。 主题识别系统以一组初始关键字开始，并识别每个关键字的语言模式。 然后，主题识别系统使用所识别的语言模式来识别与模式匹配的在线讨论的附加关键字。 然后，主题识别系统再次使用包括新确定的关键字的关键字来识别语言模式。 主题识别系统可以重复识别语言模式和关键字的过程，直到满足终止标准。
-
公开(公告)号：US20080086297A1
公开(公告)日：2008-04-10
申请号：US11538770
申请日：2006-10-04
申请人： Hua Li , Song Huang , Zheng Chen , Jian Wang
发明人： Hua Li , Song Huang , Zheng Chen , Jian Wang
IPC分类号： G06F17/28
CPC分类号： G06F17/28
摘要： A method and system for identifying expansions of abbreviations using learned weights is provided. An abbreviation system generates features for various expansions of an abbreviation and generates a score indicating the likelihood that an expansion is a correct expansion of the abbreviation. A expansion with the same number of words as letters in the abbreviation is more likely in general to be a correct expansion than an expansion with more or fewer words. The abbreviation system calculates a score based on a weighted combination of the features. The abbreviation system learns the weights for the features from training data of abbreviations, candidate expansions, and scores for the candidate expansions.
摘要翻译： 提供了一种用于使用学习的权重来识别缩写的扩展的方法和系统。 缩写系统产生缩写的各种扩展的特征，并生成表示扩展是缩写的正确扩展的可能性的分数。 与缩写中的字母相同数量的单词的扩展通常可能是具有更多或更少单词的扩展的正确扩展。 缩写系统基于特征的加权组合来计算得分。 缩写系统从候选扩展的缩写，候选扩展和分数的训练数据中学习特征的权重。
-
-
-
-
-
-
-
-
-
搜索结果
135 条记录 (耗时 0.023 秒)