Essays about: "search engines"

Showing result 1 - 5 of 98 essays containing the words search engines.

  1. 1. Challenges faced by “Pakistani entrepreneurs” in different cultural context

    University essay from Linnéuniversitetet/Institutionen för ekonomistyrning och logistik (ELO); Linnéuniversitetet/Institutionen för ekonomistyrning och logistik (ELO)

    Author : Mahroz Akhtar; Awais Mahmood; [2018]
    Keywords : Pakistani Entrepreneurs; s – Start-ups; Pakistani start-ups; Challenges for start-ups; Cultural aspects of start-ups; Immigrant entrepreneurs; Business culture in Pakistan and Sweden.;

    Abstract : Purpose – The purpose of this research paper is to explore the challenges faced by Pakistani entrepreneurs in different cultural context of Sweden and Pakistan. Design/methodology/approach – In order to collect primary data, authors has conducted six interviews of Pakistani entrepreneurs. READ MORE

  2. 2. Swedes only hate queue jumpers they don't know : A description of brand attitudes on Google's SERPs

    University essay from Linnéuniversitetet/Institutionen för marknadsföring (MF); Linnéuniversitetet/Institutionen för marknadsföring (MF); Linnéuniversitetet/Institutionen för marknadsföring (MF)

    Author : Ebba Fils; Clara Harrison; Mathilda Nilsson; [2018]
    Keywords : Attitudes; ABC-model; branding; Google; SEM; search engine; paid advertising on SERP;

    Abstract : Background: The Internet has developed the world of advertising by giving advertisers the possibility to track specific patterns among their consumers, which shows how consumers are clicking on online advertisements and what translates into sales for the brand. Lately, companies have actively starting to make use of search engines marketing (SEM). READ MORE

  3. 3. Is trust in SEM an intergenerational trait? : A study of sponsored links and generational attitudes towards them

    University essay from Högskolan i Halmstad/Akademin för ekonomi, teknik och naturvetenskap; Högskolan i Halmstad/Akademin för ekonomi, teknik och naturvetenskap

    Author : Jesper Fredlund; Timmy Biedron; [2018]
    Keywords : SEM; SEA; Search Engines; Search Behaviour; Organic links; Sponsored links;

    Abstract : Title: Is trust in SEM an intergenerational trait? Date: 2018-05-22 Level: Bachelor Thesis in International Marketing Author: Jesper Fredlund 930427 & Timmy Biedron 961128 Supervisor: Henrietta Nilson Problem formulation: How do age correlate with trust and attitude towards SEM on Google in Sweden? Purpose: The purpose of this study is to see if the Swedish Digital Natives are more likely to be trusting search engine marketing, as opposed to the older generations of Digital Immigrants, and by doing this gaining a better understanding of the attitudes towards search engines and search enginemarketing in Sweden. Theoretical framework: The theoretical framework of this paper consists of theories about BannerBlindness, Text Blindness, EHS Theory, Search Engine Marketing, Sponsored Links, Organic Links,Generations. READ MORE

  4. 4. Efficient fuzzy type-ahead search on big data using a ranked trie data structure

    University essay from Umeå universitet/Institutionen för fysik

    Author : John Bergman; [2018]
    Keywords : Approximate string matching; Fuzzy search; Type-ahead search; String similarity;

    Abstract : The efficiency of modern search engines depends on how well they present typo-corrected results to a user while typing. So-called fuzzy type-ahead search combines fuzzy string matching and search-as-you-type functionality, and creates a powerful tool for exploring indexed data. READ MORE

  5. 5. Deep Neural Networks for Context Aware Personalized Music Recommendation : A Vector of Curation

    University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)

    Author : Oktay Bahceci; [2017]
    Keywords : Information Filtering; Information Retrieval; Search Engine; Search Engines; Recommendation; Music Recommendation; Personalized Recommendation; Personalised Recommendation; Context Aware Recommendation; Recommender Systems; Statistical Learning; Artificial Intelligence; Machine Learning; Deep Learning; Neural Networks; Artificial Neural Networks; Feed Forward Neural Networks; Convolutional Neural Networks; Recurrent Neural Networks; Deep Neural Networks; Embedding;

    Abstract : Information Filtering and Recommender Systems have been used and has been implemented in various ways from various entities since the dawn of the Internet, and state-of-the-art approaches rely on Machine Learning and Deep Learning in order to create accurate and personalized recommendations for users in a given context. These models require big amounts of data with a variety of features such as time, location and user data in order to find correlations and patterns that other classical models such as matrix factorization and collaborative filtering cannot. READ MORE