Academic literature on the topic 'Lucene.net'

A business institution can promote their products in its online shop. With the promotion of online stores, consumers can find out which products are sold at the store. Consumers who are looking for a product can search based on various attributes of goods that are scattered in various fields in the database table, and can even be spread across different tables. All attributes that point to an item are collected in one document which will be searched using the Full Text Search system. Two alternatives to the Full Text Search system were selected; Lucene.Net and Sqlite Full Text Search. Before actually being used, these two search system alternatives were tested first. In document storage size, Lucene.Net is superior by 6.78 times. The speed of writing Sqlite search documents is superior by between 1,875 times to 5,197 times. In terms of key search speed, Lucene.Net was superior by between 1,169 and 1,698 times. Based on the consideration of the speed and development of Lucene.Net Core which is still in beta stage, Sqlite Full Text Search is suitable for use in the product search process in the Online Store.

Plagiarism can be categorized into several levels: carbon copy, the addition of words, word substitutions, changing active into passive sentences, and paraphrase. In this research, the detection is only performed by local similarity assessment method. This research is categorized into 3 major processes: preprocessing, candidate determination, and calculation of similarity. In preprocessing, extraction and conversion of a PDF file into XML is performed. Stopword removal and stemming are also performed in this process. For Candidates determination, the process used VSM (Vector Space Model) algorithm using Lucene.NET. It will then calculate the similarity values of the candidates. Similarity values that meet the threshold will be processed in the third stage. The next process is detecting plagiarism at the level of carbon copy. The plagiarism of the substitution level will be determined by finding synonymous with Lesk algorithm and utilizing WordNet as a language dictionary. Lesk notice the words around it, before doing the search process is synonymous with Lesk, performed first sentence extractor. From this experiment, it is concluded that the determination of synonyms using WordNet and Lesk algorithm does not seem to increase its similarity value role. This is due to the difficulty of finding plagiarism by just substituting words. However, plagiarism at the level of carbon copy can be handled with the help of sentence matching.

This master’s thesis, conducted at Sectra Medical Systems AB, investigates the feasibility of integrating a search platform, built on modern search technology, into the complex architecture of existing products. This was done through the implementation and integration of a search platform prototype, called Sectra Enterprise Search. It was built upon the search engine library Lucene.NET, written in C# for the Microsoft .NET Framework. Lucene.NET originates from the Java library Lucene, which is highly regarded and widely used for similar purposes. During the development process a lot of requirements for the search platform were identified, including high availability, scalability and maintainability. Besides full text search for information in a variety of data sources, desirable features include autocompletion and highlighting. Sectra Enterprise Search was successfully integrated within the architecture of existing products. The architecture of the prototype consists of multiple layers, with the search engine functionality at the very bottom and a web service handling all incoming request at the top. To sum up, integrating a search platform based on modern search technology into the architecture of existing products infers full control of deployment, users searching in a more intuitive manner and reasonable search response times.

Web shops today needs to be more and more responsive, where one part of this responsivenessis fast product searches. One way of getting faster searches are by searching against anindex instead of directly against a database. Network Expertise Sweden AB (Net Exp) wants to explore different methods of implementingan index in their future web shop, building upon the open-source web shop platformSmartStore.NET. Since SmartStore.NET does all of its searches directly against itsdatabase, it will not scale well and will wear more on the database. The aim was thereforeto find different solutions to offload the database by using an index instead. A prototype that retrieved products from a database and made them searchable through anindex was developed, evaluated and implemented. The prototype indexed the data with aninverted index algorithm, and was made searchable with a search algorithm that mixed typeboolean queries with normal queries.
Webbutiker idag behöver vara mer och mer responsiva, en del av denna responsivitet ärsnabb produkt sökningar. Ett sätt att skaffa snabbare sökningar är genom att söka mot ettindex istället för att söka direkt mot en databas. Network Expertise Sweden AB vill utforska olika metoder för att implementera ett index ideras framtida webbutik, byggt ovanpå SmartStore.NET som är öppen käll-kod. Då Smart-Store.NET gör alla av sina sökningar direkt mot sin databas, kommer den inte att skala braoch kommer slita mer på databasen. Målsättningen var därför att hitta olika lösningar somavlastar databasen genom att använda ett index istället. En prototyp som hämtade produkter från en databas och gjorde dom sökbara genom ettindex var utvecklad, utvärderad och implementerad. Prototypen indexerade datan med eninverterad indexerings algoritm, och gjordes sökbara med en sök algoritm som blandar booleskafrågor med normala frågor.

Metadata is the important information describing geographical data resources and their key elements. It is used to guarantee the availability and accessibility of the data. ISO 19115 is a metadata standard for geographical information, making the geographical metadata shareable, retrievable, and understandable at the global level. In order to cope with the massive, high-dimensional and high-diversity nature of geographical data, data mining is an applicable method to discover the metadata.

This thesis develops and evaluates an automated mining method for extracting metadata from the data environment on the Local Area Network at the National Land Survey of Sweden (NLS). These metadata are prepared and provided across Europe according to the metadata implementing rules for the Infrastructure for Spatial Information in Europe (INSPIRE). The metadata elements are defined according to the numerical formats of four different data entities: document data, time-series data, webpage data, and spatial data. For evaluating the method for further improvement, a few attributes and corresponding metadata of geographical data files are extracted automatically as metadata record in testing, and arranged in database. Based on the extracted metadata schema, a retrieving functionality is used to find the file containing the keyword of metadata user input. In general, the average success rate of metadata extraction and retrieval is 90.0%.

The mining engine is developed in C# programming language on top of the database using SQL Server 2005. Lucene.net is also integrated with Visual Studio 2005 to build an indexing framework for extracting and accessing metadata in database.