公开(公告)号：US08249583B2

公开(公告)日：2012-08-21

申请号：US13139566

申请日：2009-12-11

Applicant: Andrés Cancer Abreu ,  Carlos Gascon Navarro

Inventor： Andrés Cancer Abreu ,  Carlos Gascon Navarro

IPC: H04W24/00

CPC classification number: H04Q3/00 ,  H04Q2213/13003 ,  H04Q2213/1305 ,  H04Q2213/13349 ,  H04W24/08

Abstract: The present Invention relates to a method and to a system for identifying and characterizing the impact of network incidents on the telecommunication services offered to users. According to the invention, the system for identifying and characterizing an incident in a service offered to a user of a telecommunications network comprises an unavailability selection module (1), a consolidation module (4), an aggregation module (10), a stabilization module (12) and a notification module (14).

Abstract translation: 本发明涉及一种用于识别和表征网络事件对提供给用户的电信服务的影响的方法和系统。 根据本发明，用于识别和表征提供给电信网络的用户的服务中的事件的系统包括不可用性选择模块（1），合并模块（4），聚合模块（10），稳定模块 （12）和通知模块（14）。

公开(公告)号：US20120059785A1

公开(公告)日：2012-03-08

申请号：US12874709

申请日：2010-09-02

Applicant: Juan Moises PASCUAL LEO ,  Enrique Frias Martinez

Inventor： Juan Moises PASCUAL LEO ,  Enrique Frias Martinez

IPC: G06N5/02

CPC classification number: G06Q30/02

Abstract: The invention relates to a content recommendation method and system based on psychological factors from a use profile, which comprises: (a) a website for downloads that is accessible for the user, where said site comprises means configured for the detection of his consumption profile (1); (b) a psychographics driver (2) configured to calculate his profile in the five super traits of the Big Five model, said profile being stored in a first database (3), said data being accessible for the current query and subsequent queries; and (c) means configured to cross-match (5) the psychological profile stored in the first database (3) and the data contained in a second content database (4); all such that access preferably to those contents which best adapt to the calculated psychological profile is granted to the user.

Abstract translation: 本发明涉及一种基于使用简档的心理因素的内容推荐方法和系统，其包括：（a）用户可访问的用于下载的网站，其中所述站点包括被配置用于检测他的消费简档的装置 1）; （b）心理驱动器（2），被配置为在所述五大模型的五个超特征中计算他的简档，所述简档存储在第一数据库（3）中，所述数据可被当前查询和后续查询访问; 和（c）被配置为交叉匹配（5）存储在第一数据库（3）中的心理简档和包含在第二内容数据库（4）中的数据; 所有这些使得优选地对最适合于所计算的心理特征的那些内容的访问被授予给用户。

公开(公告)号：US20110276649A1

公开(公告)日：2011-11-10

申请号：US12968515

申请日：2010-12-15

Applicant: Josep M. Pujol ,  Georgos Siganos ,  Vijay Erramilli ,  Xiaoyuan Yang ,  Nikolaos Laoutaris ,  Parminder Chabbra ,  Pablo Rodriquez

Inventor： Josep M. Pujol ,  Georgos Siganos ,  Vijay Erramilli ,  Xiaoyuan Yang ,  Nikolaos Laoutaris ,  Parminder Chabbra ,  Pablo Rodriquez

IPC: G06F15/16

CPC classification number: H04L67/1095 ,  G06Q10/10 ,  H04L67/306

Abstract: Method, system and computer program to provide transparent scalability to Online Social Networks and better performance of its back-end databases, by an efficient partitioning of the underlying community structure and replicating of user profiles, ensuring that every user has a master or slave replica of all his neighbours on the same partition where he is located.

Abstract translation: 方法，系统和计算机程序，通过有效划分底层社区结构和复制用户配置文件，为在线社交网络提供透明的可扩展性和更好的后端数据库性能，确保每个用户都拥有主 他所在的邻居在他所在的同一个分区上。

公开(公告)号：US20110224984A1

公开(公告)日：2011-09-15

申请号：US12964976

申请日：2010-12-10

Applicant: Xavier Anguera Miro ,  Robert Macrae

Inventor： Xavier Anguera Miro ,  Robert Macrae

IPC: G10L15/12

CPC classification number: G10L15/12

Abstract: Method, system and computer program for determining the matching between a first and a second sampled signals using an improved Dynamic Time Warping algorithm, called Unbounded DTW. It uses a dynamic programming algorithm to find exact start-end alignment points, unknown a priori, being the initial subsampling of the similarity matrix made via definition of optimal synchronization points, allowing a very fast process.

Abstract translation: 使用称为无界DTW的改进的动态时间扭曲算法来确定第一和第二采样信号之间的匹配的方法，系统和计算机程序。 它使用动态规划算法来查找精确的起始对齐点，先验未知，是通过定义最佳同步点进行的相似性矩阵的初始子采样，允许非常快的过程。

公开(公告)号：US20110207430A1

公开(公告)日：2011-08-25

申请号：US12710699

申请日：2010-02-23

Applicant: Fernando DIAZ BARROSO ,  Francisco Javier Carrasco López ,  Omar Briones Vilar ,  Pablo Aguiló Pastrana

Inventor： Fernando DIAZ BARROSO ,  Francisco Javier Carrasco López ,  Omar Briones Vilar ,  Pablo Aguiló Pastrana

IPC: H04M11/00

CPC classification number: H04M15/61 ,  G06Q30/02 ,  H04M15/58 ,  H04M15/765 ,  H04M15/8066

Abstract: The invention relates to a method for optimizing the consumption of telecommunications services in user groups. The method allows analyzing in real time the effectiveness of the multiple attributes of the commercial products associated with telecommunication services offered on a telecommunications network without excess calculations having to be generated, and at the same automatically acting accordingly on those attributes, optimizing the objective functions established by the telecommunications operator in the shortest possible time.

Abstract translation: 本发明涉及一种优化用户组中电信业务消耗的方法。 该方法允许实时分析与在电信网络上提供的电信业务相关联的商业产品的多个属性的有效性，而不需要生成过多的计算，并且在相同的情况下自动地对这些属性进行动作，优化建立的目标函数 由电讯营办商在最短的时间内。

公开(公告)号：US20110197132A1

公开(公告)日：2011-08-11

申请号：US13020950

申请日：2011-02-04

Applicant: Oscar Divorra Escoda ,  David Espinola Torrent

Inventor： Oscar Divorra Escoda ,  David Espinola Torrent

IPC: G06F3/00

CPC classification number: H04L67/36 ,  H04L67/38

Abstract: The present invention provides a collaborative tool which is a distributed multi-touch cloud-connected desktop tool comprising a client application and/or webtop with an integrated immersive Natural User Interface adapted for any input device having a touch screen. Thanks to the invention users can access their desktops from everywhere, at anytime and from any capable device, as the desktop is multiplatform and can be accessed from mobile devices, web browsers or from desktops as standalone application without the necessity of a desktop computer. Thanks to the invention, users can share digital content, edit it and interact with it in a cooperative and collaborative manner while still able to individually and independently arrange objects and/or applications in each of the clients for the best convenience of each user.

Abstract translation: 本发明提供了一种协作工具，其是分布式多点云连接桌面工具，其包括客户端应用程序和/或webtop，其具有适合于具有触摸屏的任何输入设备的集成的沉浸式自然界面用户界面。 由于发明，用户可以随时随地从任何有能力的设备访问他们的桌面，因为桌面是多平台的，可以从移动设备，网络浏览器或台式机访问作为独立应用程序，而无需台式计算机。 由于本发明，用户可以以协作和协作的方式共享数字内容，编辑它并进行交互，同时还能够在每个客户端中独立地和独立地排列对象和/或应用程序，以便每个用户的最佳方便。

公开(公告)号：US20100111312A1

公开(公告)日：2010-05-06

申请号：US12610588

申请日：2009-11-02

Applicant: Helenca Duxans Barrobes ,  David Conejer Olesti ,  Xavier Anguera Miro ,  Urtzi Urdapilleta Roy

Inventor： Helenca Duxans Barrobes ,  David Conejer Olesti ,  Xavier Anguera Miro ,  Urtzi Urdapilleta Roy

IPC: H04R29/00

CPC classification number: H04H60/58 ,  H04H20/14 ,  H04H60/37 ,  H04H60/375

Abstract: Method and system of identification of at least one audiovisual advertisement in a data stream, such as a digital television broadcasting, by detecting energy drops in an audio stream of the data stream and comparing a segment of the audio stream starting at the energy drop with an audio segment of the advertisement. The comparison step requires only a few seconds of data to perform the detection. Therefore, the identification of the advertisement is provided before the end of the advertisement in the data stream.

Abstract translation: 通过检测数据流的音频流中的能量损失并且将能量损失开始的音频流的一段与一个能量下降对应的数据流中的至少一个视听广告的识别方法和系统，例如数字电视广播 广告的音频段。 比较步骤仅需要几秒钟的数据来执行检测。 因此，在数据流中的广告结束之前提供广告的识别。

公开(公告)号：US20080263014A1

公开(公告)日：2008-10-23

申请号：US12104843

申请日：2008-04-17

Applicant: Francisco Javier GARIJO MAZARIO ,  Jose SANCHEZ SANCHEZ ,  Susana JURADO APRUZZESE

Inventor： Francisco Javier GARIJO MAZARIO ,  Jose SANCHEZ SANCHEZ ,  Susana JURADO APRUZZESE

IPC: G06F7/06 ,  G06F17/30

CPC classification number: G06F16/58

Abstract: Method, device, and computer program for managing information relating to a person, including a stage of storing at least one item, wherein the stage of storing includes selecting an item which is to be saved; assigning to the item one or several identifying markers, wherein the markers are based on the human mind operation model; saving the item together with its marker or markers; obtaining a key associated to the item to subsequently retrieve the item.

Abstract translation: 用于管理与人有关的信息的方法，设备和计算机程序，包括存储至少一个项目的阶段，其中所述存储阶段包括选择要被保存的项目; 向所述物品分配一个或多个识别标记，其中所述标记基于所述人类思维操作模型; 保存项目及其标记或标记; 获得与该项目相关联的密钥以随后检索该项目。

公开(公告)号：US20220337293A1

公开(公告)日：2022-10-20

申请号：US17760628

申请日：2020-09-08

Applicant: TELEFONICA, S.A.

Inventor： Javier LORCA HERNANDO ,  Elena SERNA SANTIAGO ,  Juan Francisco ESTEBAN RIVAS

IPC: H04B7/0452 ,  H04L25/03 ,  H04B7/06

Abstract: A method and system for optimizing the performance of spatial multiplexing techniques in MU-MIMO wireless systems comprising subsectors where the presence of significant correlation between antenna elements can impair the performance of MU-MIMO techniques. The proposed solution ensures optimum selection of a specific combination of transmit antenna elements and receive antenna elements that maximizes MU-MIMO performance

公开(公告)号：US11301778B2

公开(公告)日：2022-04-12

申请号：US16359336

申请日：2019-03-20

Applicant: TELEFONICA, S.A.

Inventor： Antonio Pastor Perales ,  Diego R. Lopez ,  Alberto Mozo Velasco ,  Sandra Gomez Canaval

IPC: G06N20/00 ,  G06N5/04 ,  H04L43/026 ,  H04L43/028 ,  H04L43/067 ,  H04L43/12 ,  H04L41/16 ,  H04L41/14 ,  H04L47/10

Abstract: A system and method for training and validating ML algorithms in real networks, including: generating synthetic traffic and receiving it along with real traffic; aggregating the received traffic into network flows by using metadata and transforming them to generate a first dataset readable by the ML algorithm, comprising features defined by the metadata; labelling the traffic and selecting a subset of the features from the labelled dataset used in an iterative training to generate a trained model; filtering out a part of real traffic to obtain a second labelled dataset; and selecting a subset of features from the second labelled dataset used for validating the trained model by comparing predicted results for the trained model and the labels; repeating the steps with a different subset of features to generate another trained model until results are positive in terms of precision or accuracy.