公开(公告)号：US11880421B2

公开(公告)日：2024-01-23

申请号：US17535466

申请日：2021-11-24

Applicant: Electronics and Telecommunications Research Institute

Inventor： Yong-Jin Bae ,  Joon-Ho Lim ,  Min-Ho Kim ,  Hyun Kim ,  Hyun-Ki Kim ,  Ji-Hee Ryu ,  Kyung-Man Bae ,  Hyung-Jik Lee ,  Soo-Jong Lim ,  Myung-Gil Jang ,  Mi-Ran Choi ,  Jeong Heo

IPC: G06F16/957 ,  G06F16/31 ,  G06F16/33 ,  G06F40/205

CPC classification number: G06F16/957 ,  G06F16/316 ,  G06F16/3334 ,  G06F40/205

Abstract: Disclosed herein are an apparatus and method for providing a search service based on important sentences. The apparatus for providing a search service based on important sentences includes memory in which at least one program and a previously trained word importance measurement model are recorded and a processor for executing the program. The program may include a word importance measurement unit for measuring the importance of each of multiple words included in input text in the corresponding input text based on the word importance measurement model and a sentence importance measurement unit for measuring the importance of each of at least one sentence included in the text based on the measured importance of each of the multiple words.

公开(公告)号：US20150161517A1

公开(公告)日：2015-06-11

申请号：US14243427

申请日：2014-04-02

Applicant: ELECTRONICS AND TELECOMMUNICATIONS RESEARCH INSTITUTE

Inventor： Yong-Jin BAE ,  Hyun-Ki Kim ,  Myung-Gil Jang ,  Mi-Ran Choi ,  Jeong Heo ,  Soo-Jong Lim ,  Hyo-Jung Oh ,  Chung-Hee Lee ,  Pum-Mo Ryu ,  Yeo-Chan Yoon ,  Yoon-Jae Choi ,  Yo-Han Jo

IPC: G06N7/00 ,  H04L29/08

CPC classification number: H04L67/22 ,  G06N20/00 ,  G06Q50/01

Abstract: A method and device for predicting popularity by setting various criteria of popularity of social data spread over a social network service (SNS) including: a data collecting unit to collect previous data created during a predetermined time and created in real time from data storage associated with an SNS, a data popularity prediction resource building unit to extract user information and data information from the previous data created during the predetermined time and build a social data popularity prediction resource using the extracted user information and data information, and a popularity predicting unit to predict popularity of the social data created in real time using the data information and the user information extracted from the data created in real time and the built popularity prediction resource, in which the predicted popularity includes predicted values of at least two items among a spread amount, a popularity time, and a spread rate.

Abstract translation: 一种用于通过设定在社交网络服务（SNS）上传播的社会数据的流行度的各种标准来预测流行度的方法和装置，包括：数据收集单元，用于收集在预定时间期间创建并且实时地从与 SNS，数据流行度预测资源建立单元，用于从在预定时间期间创建的先前数据中提取用户信息和数据信息，并使用所提取的用户信息和数据信息构建社交数据流行度预测资源，以及普及预测单元来预测 使用从实时创建的数据中提取的数据信息和用户信息以及建立的流行度预测资源实时创建的社交数据的流行度，其中预测流行度包括扩展量中的至少两个项目的预测值， 流行时间和传播率。

公开(公告)号：US10037381B2

公开(公告)日：2018-07-31

申请号：US14260828

申请日：2014-04-24

Applicant: Electronics and Telecommunications Research Institute

Inventor： Pum-Mo Ryu ,  Hyun-Ki Kim ,  Sang-Kyu Park ,  Yong-Jin Bae ,  Jeong Heo ,  Hyo-Jung Oh ,  Chung-Hee Lee ,  Soo-Jong Lim ,  Myung-Gil Jang ,  Mi-Ran Choi ,  Yoon-Jae Choi ,  Yeo-Chan Yoon ,  Yo-Han Jo

IPC: G06F17/30

CPC classification number: G06F16/951 ,  G06F16/3331

Abstract: The present invention is to provide an apparatus for searching information based on Wikipedia's contents comprising: a document converting part extracting fulltext documents, section title documents, info-box documents, category documents and definition statement documents from Wikipedia original documents and generating at least one of Wikipedia documents for questions and answers; a document indexing part analyzing the Wikipedia document for questions and answers, extracting POS-based index terms from the Wikipedia document for questions and answers, and generating a Wikipedia document index for questions and answers; a question analyzing part receiving a natural language question, analyzing a question pattern, an answer pattern and a question focus from the natural language question, and extracting document search keywords; a document searching part performing document search by using the document search keywords from the Wikipedia document index for questions and answers and generating document search result from each Wikipedia document index for questions and answers; an answer extracting part extracting first answers by using information about the question pattern, the answer pattern and the question focus from the document search result; and an answer integrating part integrating and prioritizing the first answer and generating a second answer.