Browsing by Subject "information retrieval"

Now showing 1 - 4 of 4

Access status: Open Access ,
Distributed web-scale infrastructure for crawling, indexing and search with semantic support
(Wydawnictwa AGH, 2012) Dlugolinský, Štefan; Šeleng, Martin; Laclavík, Michal; Hluchý, Ladislav
In this paper, we describe our work in progress in the scope of web-scale information extraction and information retrieval utilizing distributed computing. We present a distributed architecture built on top of the MapReduce paradigm for information retrieval, information processing and intelligent search supported by spatial capabilities. Proposed architecture is focused on crawling documents in several different formats, information extraction, lightweight semantic annotation of the extracted information, indexing of extracted information and finally on indexing of documents based on the geo-spatial information found in a document. We demonstrate the architecture on two use cases, where the first is search in job offers retrieved from the LinkedIn portal and the second is search in BBC news feeds and discuss several problems we had to face during the implementation. We also discuss spatial search applications for both cases because both LinkedIn job offer pages and BBC news feeds contain a lot of spatial information to extract and process.
Access status: Open Access ,
Metody i narzędzia automatycznego przetwarzania informacji tekstowej i ich wykorzystanie w procesie zarządzania wiedzą
(Wydawnictwa AGH, 2011) Potiopa, Piotr
Tematem niniejszego artykułu jest przegląd metod i narzędzi służących reprezentacji i przetwarzaniu informacji, która jest aktualnie jednym z podstawowych środków budowania i zarządzania w każdej organizacji. Sprawne funkcjonowanie każdej instytucji uzależnione jest od dostępu do przechowywanej w niej wiedzy, jak również możliwości sprawnego jej wyszukiwania, systematyzowania i podejmowania na jej podstawie nowych decyzji.
Access status: Open Access ,
Nadzorowana kategoryzacja tekstów angielskojęzycznych
(Wydawnictwa AGH, 2010) Chmiel, Wojciech; Kadłuczka, Piotr; Jędrusik, Stanisław
Text classification is a growing area of research at the intersection of information retrieval (IR) and machine learning. The goal of text classification systems is to attach automatically labels to previously unseen electronic documents. These labels may indicate topics discussed in the document, the relevance of the document for a given user, the mailbox or newsgroup into which the document should be filed. Text categorization presents unique challenges due to the large number of attributes present in the data set, large number of training samples, and attribute dependencies. In this paper we present a supervised classification algorithm based on centroids method and decision trees. This paper presents comprehensive computational experiments examining the efficiency of proposed classification algorithms.
Access status: Open Access ,
TF-IDF inspired detection for cross-language source code plagiarism and collusion
(Wydawnictwa AGH, 2020) Karnalim, Oscar
Several computing courses allow students to choose which programming language they want to use for completing a programming task. This can lead to cross-language code plagiarism and collusion, in which the copied code file is rewritten in another programming language. In response to that, this paper proposes a detection technique which is able to accurately compare code files written in various programming languages, but with limited effort in accommodating such languages at development stage. The only language-dependent feature used in the technique is source code tokeniser and no code conversion is applied. The impact of coincidental similarity is reduced by applying a TF-IDF inspired weighting, in which rare matches are prioritised. Our evaluation shows that the technique outperforms common techniques in academia for handling language conversion disguises. Furthermore, it is comparable to those techniques when dealing with conventional disguises.