Foreword

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Proper terminology preparation is essential to efficient translation, especially when more than one translator works on a single project. Before starting the translation, each translator should receive a glossary they must use: words and expressions in the glossary must be translated as shown there. However, pre-distributed glossaries are never complete, so new terminology is always being created during the translation process. Thus the terminology of a translated book is the result of a co-operation between the terminologist and the translators.

This dictionary contains the glossaries that were created during the translation of books published by SZAK Kiadó (Bicske, Hungary). For the purpose of the dictionary, the glossaries were merged and edited. The dictionary includes glossaries from 66 volumes. These are not only works translated from English into Hungarian: the Publisher had also encouraged authors of original Hungarian works to purposely define the terminology used in their books. This resulted in bilingual and explanatory glossaries at the end of many original Hungarian books.

Together, these volumes form the bilingual parallel corpus of SZAK Kiadó (entitled the SZAK Corpus), consisting of both the original English text and the Hungarian translation of each book. The English-language subcorpus contains ca. 4 million words, while the size of the Hungarian one is ca. 5 million words (it is the original Hungarian works that make up the difference). The Publisher uses this corpus for research and development in the field of translation technology, in co-operation with Kilgray Translation Technologies.

The dictionary is entirely corpus-based, and it provides an insight into the Publisher’s translation and editorial practices. It is also very useful for translators because it contains translation hints for words and expressions occurring in up-to-date computing texts, where these expressions raised real-life translation problems. However, the dictionary is not balanced: it only contains words and expressions that occur in books published by SZAK Kiadó. No additional material was collected, so if you are reading something that SZAK Kiadó has not dealt with before, you will probably encounter terms (words and expressions) that are not present in this dictionary.

The dictionary does not distinguish between British and US English. Terms are written as they had occurred within the original text. However, in most cases this means that the US English form is used.

There are also many entries where the headword is a message or command in a computer program. The equivalents for these are taken from the localised (Hungarian) version of the program. These entries are marked with a special symbol (see the Dictionary Entry Guide on the cover (inside). Here, Hungarian equivalents are written in their original spelling that was not corrected.

The new edition of the Dictionary contains 26,292 entries, grouped into 8,624 expression groups. Some entries were grouped into more than one expression group; physically, the Dictionary contains more than 47,500 entries. However, almost half of these are repetitions. Redundant grouping makes the Dictionary easier to use because an expression can be found by looking up almost any of its words.

The entry structure is shown in the figure on the inside of the front cover.
 

Making the Dictionary

Throughout the dictionary-making process, computational means were used. To prepare terminology for two of the volumes in the corpus, we have used methods of automatic term extraction. In addition, the creation of glossaries has also been facilitated by the terminology features of the memoQ translation environment: translators working together over the Internet could add their terms to a shared term base -- which was continuously monitored and reviewed by the reviewer of the translation itself.

We have edited the dictionary contents using database management and spreadsheet tools. From the tabular representation, we have then converted the material into XML format.  This XML format is the basis for the electronic version of the Dictionary, available online at http://www.szak.hu/szotar. The printed version was also derived from the XML database, using XSLT technology.  Thus the Dictionary was completed in less than six weeks – from collecting the material to forwarding it to the printers. These six weeks, however, do not include the time spent on producing the individual terminological glossaries for the original books because that process had been carried out continuously since the release of the previous edition.
 

The Online Version

The online version of the dictionary is available at the website of SZAK Publishers: http://www.szak.hu/szotar. The online dictionary is fully interactive, and offers full-text searching. From May 2011 onwards, the dictionary is available only to those who purchased the printed dictionary. To use the online dictionary, you need to specify your e-mail address, and the serial number found at the back of this volume.
 

Acknowledgements

Due to space limitations, we cannot list all volumes whose terminology is included in the dictionary. However, if you look at the Publisher’s Web site (http://www.szak.hu), you can view the entire backlist, which could have been copied here in its entirety, perhaps omitting one or two titles.

Although we have limited space, we must list those who contributed to the production of books related to this Dictionary, as authors, translators, terminologists, reviewers or editors – these people are in fact the real authors of this Dictionary (names are listed after the Hungarian fashion, the surname first, then the ‘first’ name):

Albert István, Baksáné Varga Erika, Balaskó Attila, Balássy György, Balogh Péter, Bánki Máté, Bányász Gábor, Bátyai Krisztián, Benedek Zoltán, Berényi Zsolt, Bezzegh Petra, Böröczky Szabolcs, Charaf Hassan, Csapó Ádám, Csernus Edina, Cserny László, Dávid Ákos, Dávid Zoltán, Deák Csaba, Dévai István, Domoszlai László, Dzurdzik Ádám, Egenhoffer Norbert, Ekler Péter, Endrédi Gabriella, Erdélyi Tibor, Erdész Jenő, Erdős Anikó, Erős Szilvia, Forstner Bertalan, Fóti Marcell, Füstös János, Füzessy Tamás, Gabányi Endre, Gábriel Zoltán, Gajda András, Gál Balázs, Gál Péter, Gál Tamás, Gál Tibor, Gincsai Gábor, Grezner Ferenc, Gyimesi Csaba, Györke István, Herczeghné Erős Melinda, Hevesi Nelli, Horváth Ádám, Horváth Brigitta, Hursán Dániel, Igliczki István, Imre Gábor, Iváncsy Renáta, Iváncsy Tamás, Jarecsni László, Juhász Gergely, Kalina András, Kallósné Molnár Krisztina, Kálmán László, Kárpáti Krisztián, Kelényi Imre, Kereskényi Róbert, Kincse Szabolcs, Kis Ádám, Kis Balázs, Kis Katalin, Kis-Menyhárt Andrea, Kisné Kalina Valéria, Kiss András, Kiss Gábor, Kopilovics Iván, Korb Zsuzsa, Kordás Imre, Kordásné Kenesei Andrea, Kővári Bence, Kroutil Gyula, Kuntner Bálint, Kuntner Gábor, Kupecz Márton, Laczkó Krisztina, Ládi László, Lángné Erdős Katalin, Lengyel István, Levendovszky Tihamér, Losonczy Gergely, Lovassy Zsolt, Lucza Mónika, Lucza Tamás, Mártonfi Attila, Megyeri Levente, Michnay Andrea, Mogyorósi István, Mogyorósi Istvánné, Mohácsi-Gorove Anna, Molnár Balázs, Nacsa Sándor, Nagy Gábor, Nagy Zsanett, Nemeslaki Ágnes, Neuhauser Márk, Nyisztor Károly, Ország Tamás, Pásztor Endre, Péteri Szilárd, Prószéky Gábor, Rajacsics Tamás, Rák Balázs, Reményi Zsolt, Révi Erik, Sarkadi Csaba, Sárosi Ádám, Schönhofen Péter, Seres Péter, Sima Dezső, Simon Ferenc, Smulovics Péter, Soczó Zsolt, Solti Gábor, Soós István, Srej Balázs, Sütő János, Szabó Levente, Szabó Roland, Szalay Márton, Szederkényi Gábor, Szerényi László, Szőr Péter, Tiber Melinda, Tihanyi László, Tóth Ildikó, Tóth Zoltán, Tóthfalussy Balázs, Trepák Mónika, Vadócz László, Vámossy Zoltán, Varga Ágnes, Varga Péter, Vigh Krisztina, Vlaskovits Dóra.

Special thanks go to Lengyel István, Pohl Gábor, Prószéky Gábor, and Ugray Gábor, who co-operated with us in the research of automatic term extraction.  I would also like to thank the development team of the memoQ translation environment, led by Benedek Zoltán and Juhász Sándor. From September 2005, the Publisher performs all translations using memoQ.

 

Bicske, 30 March 2011

Balázs Kis