USER SATISFACTION ANALYTICS USING MACHINE LEARNING TECHNIQUES / (Kayıt no. 289977)
[ düz görünüm ]
| 000 -BAŞLIK | |
|---|---|
| Sabit Uzunluktaki Kontrol Alanı | 02667nam a22003017a 4500 |
| 003 - KONTROL NUMARASI KİMLİĞİ | |
| Kontrol Alanı | KOHA |
| 005 - EN SON İŞLEM TARİHİ ve ZAMANI | |
| Kontrol Alanı | 20230418115911.0 |
| 008 - SABİT UZUNLUKTAKİ VERİ ÖGELERİ - GENEL BİLGİ | |
| Sabit Alan | 230317d2023 cy ||||| m||| 00| 0 eng d |
| 040 ## - KATALOGLAMA KAYNAĞI | |
| Özgün Kataloglama Kurumu | CY-NiCIU |
| Kataloglama Dili | eng |
| Çeviri Kurumu | CY-NiCIU |
| Açıklama Kuralları | rda |
| 041 ## - DİL KODU | |
| Metin ya da ses kaydının dil kodu | eng |
| 090 ## - Yerel Tasnif No | |
| tasnif no | YL 2805 |
| Cutter no | H26 2023 |
| 100 1# - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Hala, Balen Kamal |
| 245 10 - ESER ADI BİLDİRİMİ | |
| Başlık | USER SATISFACTION ANALYTICS USING MACHINE LEARNING TECHNIQUES / |
| Sorumluluk Bildirimi | BALEN KAMAL HAMA; SUPERVISOR: PROF. DR. ERBUĞ ÇELEBI |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE | |
| Date of production, publication, distribution, manufacture, or copyright notice | 2023 |
| 300 ## - FİZİKSEL TANIMLAMA | |
| Sayfa, Cilt vb. | viii, 47 sheets; |
| Boyutları | 31 cm. |
| Birlikteki Materyal | Includes CD |
| 336 ## - CONTENT TYPE | |
| Source | rdacontent |
| Content type term | text |
| Content type code | txt |
| 337 ## - MEDIA TYPE | |
| Source | rdamedia |
| Media type term | unmediated |
| Media type code | n |
| 338 ## - CARRIER TYPE | |
| Source | rdacarrier |
| Carrier type term | volume |
| Carrier type code | nc |
| 502 ## - TEZ NOTU | |
| Tez Notu | Thesis (MSc) - Cyprus International University. Institute of Graduate Studies and Research Computer Engineering Department |
| 504 ## - BİBLİYOGRAFİ NOTU | |
| Bibliyografi Notu | Includes bibliography (sheets 43-47) |
| 520 ## - ÖZET NOTU | |
| Özet notu | ABSTRACT<br/>Customer reviews of e-commerce service and products offering is a very critical and <br/>important in the business world. The e-commerce industry is driven by enormous <br/>data generation which is often collected for analysis and evaluation to gain both <br/>insight into decision making for customer purchase and also by the business <br/>organizations to enable them drive their businesses with informed decisions from <br/>customer review data. machine learning and natural language processing has gained <br/>so much technological development that it has been used in recent years to <br/>significantly contribute to the research and development of sentiment analysis of <br/>customer reviews and other forms of natural language processing. RNNs and LSTM <br/>in particular have been identified through research literature as a suitable deep <br/>machine learning models suitable for natural language processing due to their <br/>recurrent and sequential processing of data because natural language is also a <br/>sequential process. This study was carried out using LSTM recurrent neural network <br/>for Amazon polarity dataset classification, the study also applied the use natural <br/>language processing techniques of stemming and lemmatization which has shown <br/>great performance improvement compared on the experiment results, the results of <br/>this study was reported with an accuracy of 96%.<br/>Keywords: Amazon Customer Reviews, Deep Learning, LSTM, Natural Language <br/>Processing, Recurrent Neural Network |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Customer services |
| Alt başlık biçimi | Dissertations, Academic |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Deep learning (Machine learning) |
| Alt başlık biçimi | Dissertations, Academic |
| 650 #0 - KONU BAŞLIĞI EK GİRİŞ - KONU TERİMİ | |
| Konusal terim veya coğrafi ad | Natural language processing (Computer science) |
| Alt başlık biçimi | Dissertations, Academic |
| 700 1# - EK GİRİŞ - KİŞİ ADI | |
| Yazar Adı (Kişi adı) | Çelebi, Erbuğ |
| İlişkili Terim | supervisor |
| 942 ## - EK GİRİŞ ÖGELERİ (KOHA) | |
| Sınıflama Kaynağı | Dewey Onlu Sınıflama Sistemi |
| Materyal Türü | Thesis |
| Geri Çekilme Durumu | Kayıp Durumu | Sınıflandırma Kaynağı | Kredi için değil | Koleksiyon Kodu | Kalıcı Konum | Mevcut Konum | Raf Yeri | Kayıt Tarih | Source of acquisition | Yer Numarası | Demirbaş Numarası | Son Görülme Tarihi | Fatura Tarihi | Materyal Türü | Genel / Bağış Notu |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Onlu Sınıflama Sistemi | Tez Koleksiyonu | CIU LIBRARY | CIU LIBRARY | Tez Koleksiyonu | 17.03.2023 | Bağış | YL 2805 H26 2023 | T3144 | 17.03.2023 | 17.03.2023 | Thesis | Computer Engineering Department | |||
| Dewey Onlu Sınıflama Sistemi | CIU LIBRARY | CIU LIBRARY | Görsel İşitsel | 17.03.2023 | Bağış | YL 2805 H26 2023 | CDT3144 | 17.03.2023 | 17.03.2023 | Suppl. CD | Computer Engineering Department |