Image and Video Searching on the World Wide Web
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An Innovative Video Searching Approach Using Video Indexing
IJCSN - International Journal of Computer Science and Network, Volume 8, Issue 2, April 2019 ISSN (Online) : 2277-5420 www.IJCSN.org Impact Factor: 1.5 An Innovative Video Searching Approach using Video Indexing 1 Jaimon Jacob; 2 Sudeep Ilayidom; 3 V.P.Devassia [1] Department of Computer Science and Engineering, Govt. Model Engineering College, Thrikkakara, Ernakulam,Kerala,, India,682021 [2] Division of Computer Engineering, School of Engineering, Cochin University of Science and Technology, Thrikkakara, Ernakulam, Kerala,, India,682022 [3] Former Principal, Govt. Model Engineering College, Thrikkakara, Ernakulam,Kerala,, India,682021 Abstract - Searching for a Video in World Wide Web has augmented expeditiously as there’s been an explosion of growth in video on social media channels and networks in recent years. At present video search engines use the title, description, and thumbnail of the video for identifying the right one. In this paper, a novel video searching methodology is proposed using the Video indexing method. Video indexing is a technique of preparing an index, based on the content of video for the easy access of frames of interest. Videos are stored along with an index which is created out of video indexing technique. The video searching methodology check the content of index attached with each video to ensure that video is matching with the searching keyword and its relevance ensured, based on the word count of searching keyword in video index. The video searching methodology check the content of index attached with each video to ensure that video is matching with the searching keyword and its relevance ensured, based on the word count of searching keyword in video index. -
SEO-A Review Sonu B
International Journal of Research and Scientific Innovation (IJRSI) | Volume V, Issue II, February 2018 | ISSN 2321–2705 SEO-A Review Sonu B. Surati, Ghanshyam I. Prajapati Department of Information Technology, Shri S’ad Vidya Mandal Institute of Technology, Bharuch, Gujarat, India Abstract— Search Engine Optimization (SEO) is the process of affecting online visibility of a website or web page. This is important to improve rank of search result for website and get more page views, which are requested by user and these users can be converted into customers. A Search Engine Optimization may target on different search engines like image, video, academic, news, industry etc. and using these engine ranks they provide better and optimized result for user. These ranks help them to view popular page among the number of page available in the (non-paid) search result. Also, SEO is to help website managers to improve traffic of website, to making site friendly, to building link, and marketing unique value of site. SEO classified in two categories as either white hat SEO or black hat SEO. White hats tend to produce results that last a long time, whereas black hats anticipate that their sites may eventually be banned either temporarily or permanently. SEO is used to improve their frames and create more economic effectiveness and social effectiveness and also they can focus on national and international searcher(s). Keywords— Search Engine Optimization, White Hat, Black Hat, Link- Building, Marketing, Website, Social Sharing, Ranking. I. INTRODUCTION Fig.1 History of SEO search engine is software that is designed to search for So using cluster k- means algorithm solve delay problems, A information on World Wide Web. -
A Method for a Small Web Site to Add Some Video Sharing Features
LiU-ITN-TEK-A--08/013--SE A method for a small web site to add some video sharing features Juan Lucas Madurga Martín-Serrano 2008-01-31 Department of Science and Technology Institutionen för teknik och naturvetenskap Linköping University Linköpings Universitet SE-601 74 Norrköping, Sweden 601 74 Norrköping LiU-ITN-TEK-A--08/013--SE A method for a small web site to add some video sharing features Examensarbete utfört i datavetenskap vid Tekniska Högskolan vid Linköpings unversitet Juan Lucas Madurga Martín-Serrano Examinator Bengt Lennartsson Norrköping 2008-01-31 Upphovsrätt Detta dokument hålls tillgängligt på Internet – eller dess framtida ersättare – under en längre tid från publiceringsdatum under förutsättning att inga extra- ordinära omständigheter uppstår. Tillgång till dokumentet innebär tillstånd för var och en att läsa, ladda ner, skriva ut enstaka kopior för enskilt bruk och att använda det oförändrat för ickekommersiell forskning och för undervisning. Överföring av upphovsrätten vid en senare tidpunkt kan inte upphäva detta tillstånd. All annan användning av dokumentet kräver upphovsmannens medgivande. För att garantera äktheten, säkerheten och tillgängligheten finns det lösningar av teknisk och administrativ art. Upphovsmannens ideella rätt innefattar rätt att bli nämnd som upphovsman i den omfattning som god sed kräver vid användning av dokumentet på ovan beskrivna sätt samt skydd mot att dokumentet ändras eller presenteras i sådan form eller i sådant sammanhang som är kränkande för upphovsmannens litterära eller konstnärliga anseende eller egenart. För ytterligare information om Linköping University Electronic Press se förlagets hemsida http://www.ep.liu.se/ Copyright The publishers will keep this document online on the Internet - or its possible replacement - for a considerable time from the date of publication barring exceptional circumstances. -
IASA Journal 35 CS3-2.Indd
Article The VIDI-Video semantic video search engine Marco Bertini, Università di Firenze, Italy, Marco Rendina, Fondazione Rinascimento Digitale, Italy128 Introduction Video is becoming vital to society and economy. It plays a key role in information distribution and access, and it is also becoming the natural form of communication on the Internet and via mobile devices. The massive increase in digital audiovisual information will pose high demands on advanced storage and retrieval engines, and it is certain that consumers and professionals will need advanced storage and search technologies for the management of large-scale video assets. Current search engines, however, mostly rely on keyword-based access that uses manually annotated metadata, and do not allow for content-based search of images or videos. At present, even state-of-the-art video search engines are able to annotate automatically only a limited set of semantic concepts, and retrieval is usually allowed using only a keyword-based approach based on a lexicon. The VIDI-Video project, funded in the 6th Framework Program by the EU, has taken on the challenge of creating substantially enhanced semantic access to video. The project has aimed to integrate and develop state-of-the-art components from many technologies — such as machine learning, audio event detection, video processing, visual feature processing, knowledge modeling and management, interaction and visualization — into a fully implemented audiovisual search engine, combining large numbers of audiovisual concepts and -
A Scalable Video Search Engine Based on Audio Content
A Scalable Video Search Engine Based on Audio Content Indexing and Topic Segmentation Julien Lawto, Jean-Luc Gauvain, Lori Lamel, Gregory Grefenstette, Guillaume Gravier, Julien Despres, Camille Guinaudeau, Pascale Sébillot To cite this version: Julien Lawto, Jean-Luc Gauvain, Lori Lamel, Gregory Grefenstette, Guillaume Gravier, et al.. A Scalable Video Search Engine Based on Audio Content Indexing and Topic Segmentation. 2011 Networked and Electronic Media (NEM) Summit : Implementing Future Media Internet, Sep 2011, Torino, Italy. 160 p. hal-00645228 HAL Id: hal-00645228 https://hal.archives-ouvertes.fr/hal-00645228 Submitted on 27 Nov 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. A SCALABLE VIDEO SEARCH ENGINE BASED ON AUDIO CONTENT INDEXING AND TOPIC SEGMENTATION Julien LawTo1, Jean-Luc Gauvain2, Lori Lamel2, Gregory Grefenstette1, Guillaume Gravier3, Julien Despres4, Camille Guinaudeau3, Pascale Sebillot3 1Dassault Systèmes/Exalead, Paris, France; 2LIMSI, Orsay, France ; 3IRISA, Rennes, France ; 4Vocapia Research, Orsay, France E-mail: 13ds.com, 2limsi.fr, 3irisa.fr, 4vocapia.com Abstract: One important class of online videos is that Most current video search engines rely, in a large part, on of news broadcasts. Most news organisations provide indexing the textual metadata associated with the video near-immediate access to topical news broadcasts over (title, tags, surrounding page-text). -
Search Engine Optimization and the Connection with Knowledge Graphs
FACULTY OF EDUCATION AND BUSINESS STUDIES Department of Business and Economics Studies Search Engine Optimization and the connection with Knowledge Graphs Milla Marianna Hietala Oliver Marshall 2021 Student thesis, Master degree (one year), Credits Business Administration Master Programme in Business Administration (MBA): Business Management Master Thesis in Business Administration 15 Credits Supervisor: Ehsanul Huda Chowdhury Examiner: Maria Fregidou-Malama Abstract Title: Search Engine Optimization and the connection with Knowledge Graphs Level: Thesis for Master’s Degree in Business Administration Authors: Milla Marianna Hietala and Oliver Marshall Supervisor: Ehsanul Huda Chowdhury Examiner: Maria Fregidou-Malama Date: 28-01-2021 Aim: The aim of this study is to analyze the usage of Search Engine Optimization and Knowledge Graphs and the connection between them to achieve profitable business visibility and reach. Methods: Following a qualitative method together with an inductive approach, ten marketing professionals were interviewed via an online questionnaire. To conduct this study both primary and secondary data was utilized. Scientific theory together with empirical findings were linked and discussed in the analysis chapter. Findings: This study establishes current Search Engine Optimization utilization by businesses regarding common techniques and methods. We demonstrate their effectiveness on the Google Knowledge Graph, Google My Business and resulting positive business impact for increased visibility and reach. Difficulties remain in accurate tracking procedures to analyze quantifiable results. Contribution of the thesis: This study contributes to the literature of both Search Engine Optimization and Knowledge Graphs by providing a new perspective on how these subjects have been utilized in modern marketing. In addition, this study provides an understanding of the benefits of SEO utilization on Knowledge Graphs. -
100+ Alternative Search Engines You Should Know by Kay Tan
100+ Alternative Search Engines You Should Know By Kay Tan. Filed in Tools Ads by Google Web Site Optimizer Tooloptimizely.com/Web_Optimizer_ToolThe Hottest Web Site Optimizer Tool on the Planet. Test it out! Google is the most powerful search engine available, but when it comes to searching for something specific, Google may churn out general results for some. For instance, a search for a song in Google may return the singer, the lyrics and even fan sites – depending on the keywords you entered. This is when niche-specific search engines comes into the picture. These search engines allows you to search for the things you’re looking for, and because they are more focused, their results tend to be more accurate. E-books & PDF files, audio & music, videos, etc. are probably the most commonly searched items everyday and with this list, you’ll be able to locate them easily from now on. Enjoy! E-Book & PDF Search Engine PDF Searcher Pdf Searcher is a pdf and ebook search engine. You can search and download every ebook or pdf for free! PDFGeni PDFGeni is a dedicated pdf search engine for PDF ebooks, sheets, forms and documents. Data-Sheet Data-Sheet is a pdf ebook datasheet manual search engine where you can search any ebook datasheet pdf files and download. PDFDatabase PDF Database is a new search engine which uses a unique algorithm to search for pdf and doc files from all over the web quickly and efficiently. PDF Search Engine PDF Search Engine is a book search engine search on sites, forums, message boards for pdf files. -
Image Indexing and Retrieval
DRTC Workshop on Digital Libraries: Theory and Practice March 2003 DRTC, Bangalore Paper: F Image Indexing and Retrieval Md. Farooque Documentation Research and Training Centre Indian Statistical Institute Bangalore-560 059 email: [email protected] Abstract The amount of pictorial data has been growing enormously with the expansion of WWW. From the large number of images, it is very important for users to retrieve required images via an efficient and effective mechanism. To solve the image retrieval problem, many techniques have been devised addressing the requirement of different applications. Problem of the traditional methods of image indexing have led to the rise of interest in techniques for retrieving images on the basis of automatically derived features such as color, texture and shape… a technology generally referred as Content-Based Image Retrieval (CBIR). After decade of intensive research, CBIR technology is now beginning to move out of the laboratory into the marketplace. However, the technology still lacks maturity and is not yet being used in a significant scale. Paper:F Md. Farooque 1. INTRODUCTION Images can be indexed and retrieved by textual descriptors and by image content. In textual queries, words are used to retrieve images or image sets, and in visual queries (content-based retrieval), images or image sets are retrieved by visual characteristics such as color, texture, and shape. Image retrieval strategies based on either text-based or content-based retrieval alone have their limitations. Images are often subject to a wide range of interpretations, and textual descriptions can only begin to capture the richness and complexity of the semantic content of a visual image. -
ELFIQ APP OPTIMIZER White Paper V1.03 - May 2015 CONTENTS Introduction
ELFIQ APP OPTIMIZER White Paper V1.03 - May 2015 CONTENTS Introduction ...............................................................................................................................................................................3 Signature-Based Recognition vs. ACL’s ................................................................................................................3 Detection Engine ...................................................................................................................................................................3 Using Groups or Individual Applications .............................................................................................................3 Actions Once an Application is Detected ...........................................................................................................3 Appendix A: Application List ........................................................................................................................................ 4 martellotech.com elfiq.com 2 INTRODUCTION The Elfiq AppOptimizer is designed to give organizations full control over their existing and future bandwidth, guaranteeing key applications such as Citrix XenDesktop or Skype get priority treatment and undesirables such as peer-to-peer file transfers or games are limited or no longer permitted. It is an add-on-module that provides application-layer deep packet inspection (layer 7) classification and control, including Mobile, Social Networking, P2P, Instant Messaging, -
Search Computing Cover.Indd
Search Computing Business Areas, Research and Socio-Economic Challenges Media Search Cluster White Paper European Commission European SocietyInformation and Media LEGAL NOTICE By the Commission of the European Communities, Information Society & Media Directorate-General, Future and Emerging Technologies units. Neither the European Commission nor any person acting on its behalf is responsible for the use which might be made of the information contained in the present publication. The European Commission is not responsible for the external web sites referred to in the present publication. The views expressed in this publication are those of the authors and do not necessarily reflect the official European Commission view on the subject. Luxembourg: Publications Office of the European Union, 2011 ISBN 978-92-79-18514-4 doi:10.2759/52084 © European Union, July 2011 Reproduction is authorised provided the source is acknowledged. © Cover picture: Alinari 24 ORE, Firenze, Italy Printed in Belgium White paper: Search Computing: Business Areas, Research and Socio-Economic Challenges Search Computing: Business Areas, Research and Socio- Economic Challenges Media Search Cluster White Paper Media Search Cluster - 2011 Page 1 White paper: Search Computing: Business Areas, Research and Socio-Economic Challenges Coordinated by the CHORUS+ project co-funded by the European Commission under - 7th Framework Programme (2007-2013) by the –Networked Media and Search Systems Unit of DG INFSO Media Search Cluster - 2011 Page 2 White paper: Search Computing: -
An Effective Information Retrieval Using Video Search Engines
Pacific Business Review International Volume 11 Issue 6, December 2018 Article Section An Effective Information Retrieval Using Video Search Engines Deepika Sagar Department of Computer Science and Engineering Manav Rachna International Institute of Research & Studies Jwngfu Brahma Department of Computer Science and Engineering Manav Rachna International Institute of Research & Studies Shobha Tyagi Department of Computer Science and Engineering, Manav Rachna International Institute of Research & Studies Abstract Information retrieval is a field that relates to the way of collecting, managing and retrieving data using different techniques. In this paper we have discussed the background activities through which the information is provided to the user in the form of multimedia content. Effective retrieval of information includes use of detectors and trackers that tracks the information on the basis of the logs of the previous searches. A video search engine working depends upon the operations such as crawling, indexing and finally ranking. Various ranking based criteria are involved to retrieve the best result to the user from the large quest of data. The main purpose of the use of various techniques within a search engine is to support and manage a large number of audio-visual contents. Search engine optimization is a well practice technique to provide the ranking and assigning the appropriate position to the sites over a search engine. This paper represents the various works done by different researchers in the field of information retrieval and the future use of the video search engines along with the current trends and technologies used by different video search engines. Keywords: Video search engines, Detectors, Trackers, Word recognition, Ranking, Search Engine Optimization Introduction description of the visual data. -
Web-Scale Multimedia Search for Internet Video Content
CARNEGIE MELLON UNIVERSITY Web-scale Multimedia Search for Internet Video Content Lu Jiang CMU-LTI-17-003 Language and Information Technologies School of Computer Science Carnegie Mellon University 5000 Forbes Avenue, Pittsburgh, PA, 15213 www.lti.cs.cmu.edu Thesis Committee: Dr. Alex Hauptmann, Carnegie Mellon University Dr. Teruko Mitamura, Carnegie Mellon University Dr. Louis-Philippe Morency, Carnegie Mellon University Dr. Tat-Seng Chua, National University of Singapore Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Language and Information Technologies c 2017 Lu Jiang Abstract The Internet has been witnessing an explosion of video content. According to a Cisco study, video content accounted for 64% of all the world’s internet traffic in 2014, and this percentage is estimated to reach 80% by 2019. Video data are becoming one of the most valuable sources to assess information and knowledge. However, existing video search solutions are still based on text matching (text-to-text search), and could fail for the huge volumes of videos that have little relevant metadata or no metadata at all. The need for large-scale and intelligent video search, which bridges the gap between the user’s information need and the video content, seems to be urgent. In this thesis, we propose an accurate, efficient and scalable search method for video content. As opposed to text matching, the proposed method relies on automatic video content understanding, and allows for intelligent and flexible search paradigms over the video content (text-to-video and text&video-to-video search). It provides a new way to look at content-based video search from finding a simple concept like “puppy” to searching a complex incident like “a scene in urban area where people running away after an explosion”.