Identifying the Concepts That Are Searchable with Keywords in Code Search Engines

Author(s):  
Toshihiro Kamiya
2016 ◽  
Vol 22 (1) ◽  
pp. 259-291 ◽  
Author(s):  
Haoran Niu ◽  
Iman Keivanloo ◽  
Ying Zou

2021 ◽  
Author(s):  
Carlos Eduardo C. Dantas ◽  
Marcelo A. Maia

Code search engines usually use readability feature to rank code snippets. There are several metrics to calculate this feature, but developers may have different perceptions about readability. Correlation between readability and understandability features has already been proposed, i.e., developers need to read and comprehend the code snippet syntax, but also understand the semantics. This work investigate scores for understandability and readability features, under the perspective of the possible subjective perception of code snippet comprehension. We find that code snippets with higher readability score has better comprehension than lower ones. The understandability score presents better comprehension in specific situations, e.g. nested loops or if-else chains. The developers also mentioned writability aspects as the principal characteristic to evaluate code snippets comprehension. These results provide insights for future works in code comprehension score optimization.


2017 ◽  
pp. 030-050
Author(s):  
J.V. Rogushina ◽  

Problems associated with the improve ment of information retrieval for open environment are considered and the need for it’s semantization is grounded. Thecurrent state and prospects of development of semantic search engines that are focused on the Web information resources processing are analysed, the criteria for the classification of such systems are reviewed. In this analysis the significant attention is paid to the semantic search use of ontologies that contain knowledge about the subject area and the search users. The sources of ontological knowledge and methods of their processing for the improvement of the search procedures are considered. Examples of semantic search systems that use structured query languages (eg, SPARQL), lists of keywords and queries in natural language are proposed. Such criteria for the classification of semantic search engines like architecture, coupling, transparency, user context, modification requests, ontology structure, etc. are considered. Different ways of support of semantic and otology based modification of user queries that improve the completeness and accuracy of the search are analyzed. On base of analysis of the properties of existing semantic search engines in terms of these criteria, the areas for further improvement of these systems are selected: the development of metasearch systems, semantic modification of user requests, the determination of an user-acceptable transparency level of the search procedures, flexibility of domain knowledge management tools, increasing productivity and scalability. In addition, the development of means of semantic Web search needs in use of some external knowledge base which contains knowledge about the domain of user information needs, and in providing the users with the ability to independent selection of knowledge that is used in the search process. There is necessary to take into account the history of user interaction with the retrieval system and the search context for personalization of the query results and their ordering in accordance with the user information needs. All these aspects were taken into account in the design and implementation of semantic search engine "MAIPS" that is based on an ontological model of users and resources cooperation into the Web.


Author(s):  
Valian Yoga Pudya Ardhana ◽  
Ahmad Wilda Yulianto

Blog as one of the media applicationson the Internethas been used all aroundIndonesia. The user wasnot limited  by age,ranging from children to the elderly. A lot of people notrealize that blogs can beoptimizedso thatthe bloggettingtoppositionsin search engines. Metatagwasone ofoptimization techniquesinSearch Engine Optimization (SEO).The main target washow to increaseblogtraffi requests. Afteroptimization, the next stepwasmonitoring, whichaims to determinethe extent to whichthe success ofoptimizationhas been done onSEO.The resultwas ablog sitegettingtoppositionsinthe search enginesandthe monitoring process resultsindicatethat thetitleand content was veryappropriatethat was 100%, description and contentwere alsoappropriatethat was 91%.


2020 ◽  
pp. 40-50
Author(s):  
A. Nikitina

Analysis of literature data presented in search engines — Elibrary, PubMed, Cochrane — concerning the risk of developing type I allergic reactions in patients with blood diseases is presented. It is shown that the most common cause of type I allergic reactions is drugs included in the treatment regimens of this category of patients. The article presents statistics on the increase in the number of drug allergies leading to cases of anaphylactic shock in patients with blood diseases. Modern methods for the diagnosis of type I allergic reactions in vivo and in vitro are considered.


Author(s):  
Radovan Bačík ◽  
Mária Oleárová ◽  
Martin Rigelský

The development of the Internet and the current technologies have contributed to a significant progress in the consumer shopping process. Today, shopping decisions are more intuitive and much easier to make. E-shops, search engines, customer reviews and other similar tools reduce costs of searching for products or product information, thus boosting the habit of searching for information on the Internet - "Research Shopper Phenomenon" (Verhoef et al. 2007). According to Verhoef et al. (2015), this phenomenon leads to a phenomenon where consumers search for product information using one channel (Internet) and then make a purchase through another channel (brick-and-mortar shop). Heinrich and Thalmair (2013) refer to this effect as the "research online, purchase offline" or "ROPO" effect for short. This phenomenon can also be observed in reverse. Keywords: customer behavior, research online – purchase offline, association analysis


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