Code completion systems act both as a way to decrease typing and as a way to easily access documentation, both implicit and explicit. The former is typically done by completing known variable or function names, while the latter is done by providing a list of possible completions or by providing convenient views of or access to documentation. Because static type information makes these goals possible and feasible for qualifying languages, many improvements to completion systems are focused on improving the order of results or trimming less-valuable results. It follows that almost all validation techniques for this work have focused on proving how well a completion system can put a desired result at the top of the list. However, because of the lack of static type information in dynamically-typed languages, achieving the aforementioned goals is much harder, and many of the completion suggestions may even result in compile-time or runtime crashes. Unfortunately, of the work done on creating completers for these languages, little validation work has been done, making it hard to determine what improvements can be made. This thesis provides two validation techniques that provide information both on how well completion suggestions are ordered and also which completion suggestions result in errors. This information will be used to guide the development and evolution of a completion system for the Racket programming language.

Submitted by Victor Oliveira (victor.oliveira023@gmail.com) on 2018-11-16T12:15:38Z No. of bitstreams: 1 Mestrado (2).pdf: 3223397 bytes, checksum: 2c4550dd364e7fa71ca5d5a76b209159 (MD5) / Rejected by Secretaria PPGI (secretariappgi@icomp.ufam.edu.br), reason: O arquivo apresentado não contém a Ficha Catalográfica nos moldes requeridos pela UFAM. O problema pode ser sanado através do link: http://fichacatalografica.ufam.edu.br/fichacatalografica/ficha/create. on 2018-11-16T12:35:49Z (GMT) / Submitted by Victor Oliveira (victor.oliveira023@gmail.com) on 2018-11-17T19:33:27Z No. of bitstreams: 1 Mestrado-merged.pdf: 3210603 bytes, checksum: 4fea5a7049497b21bd4c3d65b5a740c0 (MD5) / Approved for entry into archive by Secretaria PPGI (secretariappgi@icomp.ufam.edu.br) on 2018-11-19T17:31:25Z (GMT) No. of bitstreams: 1 Mestrado-merged.pdf: 3210603 bytes, checksum: 4fea5a7049497b21bd4c3d65b5a740c0 (MD5) / Approved for entry into archive by Divisão de Documentação/BC Biblioteca Central (ddbc@ufam.edu.br) on 2018-11-19T19:41:51Z (GMT) No. of bitstreams: 1 Mestrado-merged.pdf: 3210603 bytes, checksum: 4fea5a7049497b21bd4c3d65b5a740c0 (MD5) / Made available in DSpace on 2018-11-19T19:41:51Z (GMT). No. of bitstreams: 1 Mestrado-merged.pdf: 3210603 bytes, checksum: 4fea5a7049497b21bd4c3d65b5a740c0 (MD5) Previous issue date: 2018-08-28 / The number of people who buy products on e-commerce sites has been growing in recent years. The ease and comfort coupled with the growing security of the websites made it possible for more people to buy products with just a few clicks. In this universe, one of the first systems that a user encounters in the purchase process is the Automatic Query Complement, which suggests queries and products for each letter entered in the search box by the buyer. Knowing which queries to suggest to each letter typed and sorting them in the best possible way is the challenge of this system. This work focuses on knowing the best source of these queries and examines strategies for sorting queries in E-Commerce. In all of our research we did not find a paper that studies this theme in this scenario, making this work the pioneer in the subject. The strategies implemented in this paper were tested in Brazilian and Latin American retail real stores. The results were different in each store. The MRR at a Brazilian cosmetics store, for example, using one of the strategies developed in this paper, reached almost 0.8 for prefixes with three typed letters and 0.6 for an Appliances store with the same prefix size. / O número de pessoas que compram produtos em sites de comércio eletrônico vem crescendo nos últimos anos. A facilidade e conforto aliado à crescente segurança dos sites possibilitou que mais pessoas comprem produtos com apenas alguns cliques. Neste universo, um dos primeiros sistemas que um usuário se depara no processo de compra é o Complemento Automático de Consultas, que sugere consultas e produtos a cada letra digitada na caixa de busca pelo comprador. Saber quais consultas sugerir a cada letra digitada e ordená-las da melhor forma possível é o desafio deste sistema. Este trabalho se concentra em saber qual é a melhor fonte de geração dessas consultas e estuda estratégias de ordenação destas no cenário do E-Commerce. Em toda nossa pesquisa não achamos um trabalho que estuda esse tema neste cenário específico, fazendo este trabalho ser o pioneiro no assunto. As estratégias implementadas neste trabalho foram testadas em lojas reais do varejo online brasileiro e latino-americano e os resultados foram diferentes em cada loja. O MRR em uma loja brasileira de cosméticos, por exemplo, usando uma das estratégias deste trabalho, atingiu quase 0,8 para prefixos com três letras digitadas e 0,6 para uma loja de Eletrodomésticos com o mesmo tamanho de prefixo.

The suggester functionality is an important feature of modern search engines. The aim of the thesis is to implement it for the OpenGrok project. The OpenGrok search engine is based on Apache Lucene and supports its query syntax. Presented suggester implementation supports this query syntax and provides suggestions not only for prefixes but also for wildcards, regular expressions, or phrases. The implementation also takes into account the possibility of grouping queries. That means, if one query is already specified and user is typing another query, then the first query will restrict the suggestions for the second query. The promotion of specific suggestions is based on the underlying Lucene index data structure and previous searches of the users.

「民以食為天」，飲食與我們的生活息息相關。近年來由於食安風暴肆虐，自行烹煮的需求隨之高漲。然而在家自行烹煮時常會面臨不知道該烹煮什麼料理的問題，因此有便利的食譜搜尋系統對烹煮的人而言將是相當方便的。然而使用搜尋系統時，由於我們只知道想用某些特定食材進行烹煮，而不知道哪些食譜含有特定食材，因此在以少數食材進行查詢時不免會得到過多的食譜結果而難以快速找到喜好的食譜。我們建立了一個食譜搜尋的自動完成機制，並依照該機制實做出了食譜搜尋引擎。使用者使用系統進行搜尋時，我們將會依照使用者輸入的食材尋找適合搭配的食材推薦給使用者，幫助使用者在查詢時使用更完整的Query讓搜尋系統可以找到更少更精準的食譜，幫助使用者更快的找到喜歡的食譜。然而只推薦搭配性食材，可能會推薦出與Query中的食材是替代關係的食材，也就是通常不會一起出現的食材，因此我們也進行了替代性食材的研究。給定由兩個食材組成的食材配對，我們研究如何自動的判斷替代性食材。我們將問題轉化成分類問題來解決，並使用One-Class Classification的技術解決分類問題中的Imbalanced Problem。我們使用f1-score觀看One-Class Classification與傳統分類器的比較。經實驗測試，One Class Classification與傳統分類器相比，One Class Classification較能協助我們解決Imbalanced Problem。

In this work I argue that field of text search has focused mostly on long text documents, but there is a growing need for efficient short text search, which has different user expectations. Due to this reduced data set size requirements different algorithmic techniques become more computationally affordable. The focus of this work is on approximate and prefix search and purely text based ranking methods, which are needed due to lower precision of text statistics on short text. A basic prototype search engine has been created using the researched techniques. Its capabilities were demonstrated on example search scenarios and the implementation was compared to two other open source systems representing currently recommended approaches for short text search problem. The results show feasibility of the implemented prototype regarding both user expectations and performance. Several options of future direction of the system are proposed.