Sökning: "Keyword Clustering"

Visar resultat 1 - 5 av 6 uppsatser innehållade orden Keyword Clustering.

  1. 1. Advancing Keyword Clustering Techniques: A Comparative Exploration of Supervised and Unsupervised Methods : Investigating the Effectiveness and Performance of Supervised and Unsupervised Methods with Sentence Embeddings

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Filippo Caliò; [2023]
    Nyckelord :Keyword Clustering; Supervised Learning; Unsupervised Learning; Cluster Labels; Natural Language Processing; Sentence Embeddings; Nyckelord Klustring; övervakad inlärning; oövervakad inlärning; klustermärkning; naturlig språkbehandling; Inbäddning av meningar;

    Sammanfattning : Clustering keywords is an important Natural Language Processing task that can be adopted by several businesses since it helps to organize and group related keywords together. By clustering keywords, businesses can better understand the topics their customers are interested in. LÄS MER

  3. 2. Using WordNet Synonyms and Hypernyms in Automatic Topic Detection

    Kandidat-uppsats, Linnéuniversitetet/Institutionen för datavetenskap och medieteknik (DM)

    Författare :Nicko Wargärde; [2020]
    Nyckelord :topic detection; TF-IDF; SynPlusTF-IDF; keyword extraction; WordNet; synsets; synonyms; hypernyms;

    Sammanfattning : Detecting topics by extracting keywords from written text using TF-IDF has been studied and successfully used in many applications. Adding a semantic layer to TF-IDF-based topic detection using WordNet synonyms and hypernyms has been explored in document clustering by assigning concepts that describe texts or by adding all synonyms and hypernyms that occurring words have to a list of keywords. LÄS MER

  4. 3. Unsupervised Extraction and Clustering of Key Phrases from Scientific Publications

    Master-uppsats, Uppsala universitet/Institutionen för lingvistik och filologi

    Författare :Xiajing Li; [2020]
    Nyckelord :;

    Sammanfattning : Mapping a research domain can be of great significance for understanding and structuring the state-of-art of a research area. Standard techniques for systematically reviewing scientific literature entail extensive selection and intensive reading of manuscripts, a laborious and time consuming process performed by human experts. LÄS MER

  5. 4. Analysis of Remarks Using Clustering and Keyword Extraction : Clustering Remarks on Electrical Installations and Identifying the Clusters by Extracting Keywords

    Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

    Författare :Philip Stiff; [2018]
    Nyckelord :Clustering; Keyword Extraction; Free-text; Human Evaluation; Klustring; Extrahering av nyckelord; Fritext; Mänsklig utvärdering;

    Sammanfattning : Nowadays it is common for companies to sit on and gather a lot of data related to their business. The size of this data is often too large to be analyzed by hand and it is therefore becoming more and more common to automate this analysis e.g. by running machine learning methods on this data. LÄS MER

  7. 5. Detecting trolls on twitterthrough cluster analysis

    Kandidat-uppsats, KTH/Skolan för datavetenskap och kommunikation (CSC)

    Författare :Morgan Brolin; Erik Ledin; [2017]
    Nyckelord :;

    Sammanfattning : The social media platform Twitter is designed to allow users to efficiently spread informationthrough short messages that are broadcast to the world. The efficient way to spreadinformation that is in no way controlled or edited brings inherent problems with the spreadingof misinformation and other malicious activity as it can often be very difficult to establishwhat information can be considered reliable. LÄS MER