/home/dift7783/public_html/devperpus.difagroup.id/lib/SearchEngine/DefaultEngine.php:610 "Search Engine Debug 🔎 🪲"
Engine Type ⚙️: "SLiMS\SearchEngine\DefaultEngine"
SQL ⚙️: array:2 [ "count" => "select count(distinct b.biblio_id) from biblio as b left join mst_publisher as mp on b.publisher_id=mp.publisher_id left join mst_place as mpl on b.publish_place_id=mpl.place_id where b.opac_hide=0 and (b.biblio_id in(select bt.biblio_id from biblio_topic as bt left join mst_topic as mt on bt.topic_id=mt.topic_id where mt.topic like ?))" "query" => "select b.biblio_id, b.title, b.image, b.isbn_issn, b.publish_year, mp.publisher_name as `publisher`, mpl.place_name as `publish_place`, b.labels, b.input_date, b.edition, b.collation, b.series_title, b.call_number from biblio as b left join mst_publisher as mp on b.publisher_id=mp.publisher_id left join mst_place as mpl on b.publish_place_id=mpl.place_id where b.opac_hide=0 and (b.biblio_id in(select bt.biblio_id from biblio_topic as bt left join mst_topic as mt on bt.topic_id=mt.topic_id where mt.topic like ?)) order by b.last_update desc limit 10 offset 0" ]
Bind Value ⚒️: array:1 [ 0 => "%Big Data%" ]
Buku ini dibahas secara lengkap petunjuk praktis untuk melakukan text mining dengan menggunakan Pyton. bagian awal buku ini akan memberikan teori dasar tentang text mining. selanjutnya pembahasan akan dilakukan secara bertahap dengan berbagai contoh dengan menggunakan Python. semoga buku ini dapat memberikan menfaat bagi para pembaca yang ingin melakukan analisis pendapat di Internet.