scholarly journals Generalized weighted tree similarity algorithms for taxonomy trees

2016 ◽  
Vol 2016 (1) ◽  
Author(s):  
Pramodh Krishna D. ◽  
Venu Gopal Rao K.
d'CARTESIAN ◽  
2012 ◽  
Vol 1 (1) ◽  
pp. 1
Author(s):  
Halim Yosephine ◽  
Somya Ramos ◽  
Fibriani Charitas

Abstract The aim of this thesis is to give the simplicity in cooking with limited ingredients for the users by using mobile technology (J2ME). The aim of this thesis can be done by using Extended Weighted Tree Similarity Algorithm, a calculation to find out the highest weight similarity between the menu which has been inputted in the application as a database; and the inputted ingredients from the users of this application. The conclusion of this thesis is that Algorithm Extended Weighted Tree Similarity can be implemented into mobile technology (J2ME).  Keywords: extended weighted tree similarity, cooking smart, J2ME Abstrak Tujuan dari penelit ian ini adalah   memberikan kemudahan dalam memasak dengan bahan yang terbatas bagi pengguna  dengan menggunakan  teknologi  mobile  (J2ME).  Tujuan dari  tesis ini  dapat dilakukan dengan menggunakan  Algoritma  Extended Weighted Tree Similarity, perhitungan  untuk mengetahui  kesamaan  bobot  tertinggi antara menu  yang telah  diinput  dalam aplikasi  sebagai  database, dan  bahan-bahan  dimasukkan  dari  pengguna  aplikasi ini.  Kesimpulan dari  tesis ini  adalah bahwa  Algoritma Extended Weighted Tree Similarity dapat diimplementasikan ke dalam teknologi mobile (J2ME).  Kata Kunci : extended weighted tree similarity, cooking smart, J2ME


2021 ◽  
Vol 5 (1) ◽  
pp. 21-27
Author(s):  
Abdurrosyiid amrullah ◽  
Indra Gita Anugrah

As more and more documents we manage, the more difficult it is in the search process, and the need to use information retrieval becomes important. With the information retrieval system, it can help in searching for documents that match the similarity of keywords. Usually document searches usually only see the name of the document (file) being searched for by the user without paying attention to the content or metadata of the document, so that it cannot meet their information needs. Document search has several approaches, including full-text search, plain metadata search and semantic search. This study uses the Weighted Tree Similarity algorithm with the Cosine Sorensen Dice algorithm to calculate the semantic search similarity. In this study, document metadata is represented in the form of a tree that has labeled nodes, labeled branches and weighted branches. The similarity calculation on the subtree edge label uses Cosine Sorensen Dice, while the total similarity of a document uses the weighted tree similarity. The metadata structure of the document uses the taxonomy owner, description, title, disposition content and type. The result of this research is a document search application with taxonomic weight on file storage.


2021 ◽  
Vol 5 (2) ◽  
pp. 106-114
Author(s):  
Muhamad Aldi Rifai ◽  
Indra Gita Anugrah

The activity of writing scientific articles by academics at universities is one of the activities that is often carried out, but when writing scientific articles problems arise regarding the difficulty of finding ideas, literature studies, and reference sources that you want to use as references when writing. Sometimes when searching on a search engine, we have trouble finding the right document, because usually, the keywords we are looking for are not in the title section but another part of the structure. Since most search engines only match titles, other structures are usually excluded from matching. So that the search results that we do sometimes don't match what we want. In addition, usually, each scientific article has many language differences in its structure as found in the abstract section. To detect similarities through the structure of scientific articles, an algorithm is used, namely weighted tree similarity, and to detect language using the N-gram algorithm, then the cosine similarity algorithm can be used to check the level of similarity in keyword text with text in scientific articles.


2018 ◽  
Vol 11 (2) ◽  
pp. 165-176
Author(s):  
Hendra Bayu Suseno ◽  
Muhammad Fahri ◽  
Anif Hanifa Setyaningrum

ABSTRAK Berdasarkan wawancara yang dilakukan penulis dengan mubaligh sebagai narasumber, Al Lu’lu’ Wal Marjan adalah kitab yang menjadi referensi utama di kalangan mubaligh dan umat muslim karena tingkat keshahihannya yang tinggi. Walaupun kitab Al Lu’lu’ Wal Marjan menjadi refensi utama, kuesioner yang penulis sebar menunjukkan bahwa masih banyak umat muslim yang belum mengenal hadits – hadits di dalamnya. Pada umumnya penceramah selama ini menggunakan kitab sebagai dasar ceramahnya. Hal ini dirasa mempersulit penceramah karena kitab membutuhkan ruang, berat dan tidak praktis dalam melakukan pencarian. pemakalah bermaksud mendigitalisasikan kitab Al Lu’lu’ Wal Marjan kedalam aplikasi untuk membantu mubaligh menyampaikan dalil dan Juga mengenalkan hadit–hadits muttafaqun alaih kepada umat muslim pada umumnya. jumlah hadits di dalam kitab Al Lu’lu’ Wal Marjan mencapai 1906 hadits, maka dibutuhkan metode pencarian kata dengan hasil pencarian yang cepat serta dapat menyajikan urutan kemiripan untuk memberikan pilihan. Algoritma Weighted Tree Similarity yang mengelompokan indikator pencarian dengan bobot, algoritma Boyer Moore yang mencocokan keyword dengan teks Serta rumus consine yang menghitung nilai kesamaan antara tree berbobot dari keyword dengan tree database, mampu menghasilkan urutan kemiripan dengan total bobotyang diurutkan secara decending dari data yang mendekati pencarian sampai yang jauh dari data pencarian.ABSTRACT Based on interviews conducted by the author with a preacher as a resource, Al Lu'lu 'Wal Marjan is a book that became the main reference in the Muslim and Muslim preachers because of high level of highness. Even the book of Al Lu'lu 'Wal Marjan became the main reference, the questionnaire writers spread, indicating that there are still many Muslims who have not know hadith - hadith didi. In general, preachers have been using the book as the basis of his speech. This makes it difficult for speakers because the book needs space, weight and is not practical in searching. the devil's devotees digitized the book of Al Lu'lu 'Wal Marjan to the application to help preachers submit their theorem and also introduce the hadits of muttafaqun alaihong Muslim in general. the number of hadiths in the book of Al Lu'lu 'Wal Marjan reached 1906 hadith, then used to find the choice. Algorithm Moving Tree Similarity that categorizes the search indicator by weight, the Boyer Moore algorithm matching the keyword with text And the consine formula that calculates the price between the weighted tree of the keyword with the tree database, is able to generate a sequence of similarities with the accurately ranked total weight of the remote data from search data. 


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