FlickLing: a Multilingual Search Interface for Flickr - CEUR
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1. hall of fame score ranking is intended to engage a large number of users and record a large search logs which serves as the raw data for the log analysis task at iCLEF 2008 The user logs generated by the search engine in a period of around 60 days have been distrib uted among the iCLEF participants They contain information from more than 5 000 searches user image pairs conducted by more than 200 users from five continents and with a wide vari ety of language skills This is to our knowledge the largest cross language controlled search log available for scientific research and we hope that it will permit to advance in the knowledge of multilingual search processes from a user s perspective See http code google com webtoolkit 5 AJAX stands for Asynchronous JavaScript And XML 9See http www gwt ext com 10See http www turbogears org 11See http flickrapi sourceforge net 12See http www mysql com 13JSON stands for JavaScript Object Notation See http json org for further information Acknowledgements This work has been partially supported by the Regional Government of Madrid under the MAVIR Research Network S 0505 TIC 0267 and the Spanish Government under project Text Mess INES TIN2006 15265 C06 02 We would also like to thank Valent n Sama Paul Clough Jussi Karlgren and Carol Peters as early testers of preliminary versions of Flickling References 1 Gonzalo J Clough P Karlgren J 2008 Ov2. Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for saltando 2 5 sprongl Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict saltando Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for naranja 2 0 orangelapfelsine Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict naranja Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for naranja 2 gt 1lorange orangeness orange orange tree a t e Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions a t updated with PersonalDict naranj Tue May 20 15 4 for naranj Tue May 20 15 4 5 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions a 5 updated with 5 a 5 gt 2 3 orange 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions PersonalDict naranja a t ja Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for naranja 2 4 arancialarancio arancione t a t a Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict naranja Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for naranja 2 gt
3. 5 sinaasappel Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict naranja The final query is structured using Flickr syntax boolean query as in Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translatedQuery sprung OR jump OR jumping OR saltando OR saut OR salto OR sprong AND orange OR orange OR naranja OR orange OR arancia OR sinaasappel Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch query not found in DB let s use Flickr s API Tue May 20 15 45 56 2008 user_1 s51DItDdyW81j2M clsearch saved QueryCache Tue May 20 15 45 56 2008 user_1 s51DItDdyW81j2M clsearch 500 results retrieved from Flickr The user asks for some hints Tue May 20 15 48 35 2008 user_5 614sFWVeK5ETXBi getPhotoHint 1 hints showed for photo 363836021 Tue May 20 15 51 12 2008 user_5 614sFWVeK5ETXBi getPhotoHint 2 hints showed for photo 363836021 The user finds her first image and wins 10 points E having asked for some hints Score precision and average time are updated accordingly Tue May 20 15 44 45 2008 user 5 614sFWVeK5ETXBilloglclick on found it 704702302 success Tue May 20 15 44 45 2008 user_5 614sFWVeK5ETXBi foundImg photo 704702302 at 98 9274973869 secs Tue May 20 15 44 45 2008 user 5 614sFWVeK5ETXBilfoundImg score updated 10 8 10 P 1 0 T 98 9274973869 The user gives up searching photo 7983304 Tue May 20 15 49 47 2008 user_2 N
4. add new translations to her personal dictionary see Figure 5 2 2 Ranking of Results Both interfaces return a ranking containing the most relevant images for the query as shown in Figure 6 The associated titles and tags are also shown since these texts along with the image descriptions are the indexed fields against which the textual queries are launched Immediately above the ranking the system displays a multilingual set of suggested tags related to the query When the user clicks on a suggested term or a term from one of the retrieved queries the system offers two alternatives to refine the query i adding the term to the current query and ii launching a new query with the selected term When the selected term is in a foreign language the system tries to translate it into the user s preferred language to facilitate the relevance feedback process see Figure 7 On the right of each thumbnail in the ranking there are two different buttons e The second icon the document page can be used to display the complete image description if there is such as shown in Figure 8 e The first icon the bell is used to point at the target image once it is found Anytime the user can decide to quit and stop searching Next to the target image there s a button to give up Everytime the user intends to give up the system will tempt her with a hint The first hint is always the language in which the image is annotated after that hint se
5. is not know a priori by the user and second because the language skills of the actual set of users in the search log around 300 are very heterogeneous out of 5101 search sessions in 2809 cases the target language was an We used the PyStemmer module a Snowball based stemmer for English German Norwegian Italian Dutch Portuguese French Swedish See http sourceforge net projects pystemmer for further details active language for the user i e she could make queries in that language in 726 it was passive i e she could partially understand the language but not make queries and in 1566 was unknown completely unfamiliar Rather than selecting images randomly from Flickr we wanted to maintain some element of experimental control and topic variation The following points were considered during selection of the images e There should be sufficient text tags accompanying an image to facilitate the task i e we required rich annotations where possible e Ideally we wanted diverse topics in the test set and required roughly equivalent subject topics in the different language groups so the aim was to get at least one instance of a subject topic group for each of the language sets e When collecting images in different languages but with the same subject topic we aimed to find images with a similar visual perspective e The known item task should not be too hard queries for finding images were manually recorded and an indepen
6. DItDdyW81j2M clsearch tokens saltando naranja Initial query is tokenised and every single query term is stemmed and looked up in the system s dictionaries Translations and suggestions for each query term are ordered according to 1 edition distance among all possible translations 2 matchings with Flickr s related terms and 3 preferences from users personal dictionaries Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for saltando 2 0 sprungl Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict saltando Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for saltando 2 gt 1 jump jumpinglstartle jump start leap bound spring bulge bulk leaping bounce jumping Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict saltando Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for saltando 2 3 saut Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict saltando Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions for saltando 2 gt 4 salto balzo lancio saltare Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch translations and suggestions updated with PersonalDict saltando
7. FlickLing a Multilingual Search Interface for Flickr V ctor Peinado Javier Artiles Julio Gonzalo Emma Barker and Fernando L pez Ostenero NLP amp IR Group ETSI Inform tica UNED c Juan del Rosal 16 E 28040 Madrid Spain victor lsi uned es javart gmail com julio lsi uned es e barker dcs shef ac uk flopez lsi uned es Abstract In this paper we present FlickLing a multilingual search interface for Flickr designed and implemented for the CLEF 2008 interactive task FlickLing consists of two interfaces which allow to perform monolingual and mul tilingual image retrieval over the Flickr database retrieving results with images an notated in different languages From a given query entered by the user FlickLing performs automatic term by term translation into up to six languages and provides assistance for interactive query refinement and translation With the goal of collecting a large search log Flickling works as an online compet itive game where users have to find as many images as possible to obtain the highest individual and team scores Here we describe the user logs generated which has been used as a data source for the iCLEF 2008 log analysis task and contain over 5 000 complete search sessions made by over 200 users with a wide variety of language skills Categories and Subject Descriptors H 3 Information Storage and Retrieval H 3 1 Content Analysis and Indexing H 3 3 Infor mation Search and Retrieval H 4 I
8. In addition Flickling is offered to users as an online game with ranks for the best individual users and the best teams As target Flickling users were given raw images without annotations and the goal was to find in the Flickr database as many images as possible in order to obtain the highest score for them and their teams To do that users can launch monolingual and multilingual searches manipulate the automatic translations or refine their queries When a user finds the target image she obtains 25 points At any time users can quit and stop searching When they do that the system offers some hints to help finding the image If users accept the hint their score is penalised Teams and users are ranked according to their score precision percentage of found images with respect to the images seen and average time spent for each successful search session The most challenging aspect of the task besides the difficulty to describe the content of the picture and handling multiple languages is that users don t know a priori which language s were used to annotate the image when it was uploaded into Flickr In the remainder of the paper we explain the search functionalities of Flickling the query translation facilities the questionnaires posed by the system and the search logs syntax and content 2 Search Functionalities The goal of Flickling was to collect large usage logs that reflect users behaviour when facing a mul tilingual search t
9. aption language s e An advanced search mode giving more control on how Flickr is queried Other specify 9 How did you select find the best translations for your query terms e Using my knowledge of target languages whenever possible e Using additional dictionaries and other online sources e I did not pay attention to the translations I just trusted the system The results of this survey are discussed in the iCLEF 2008 overview paper 1 7 FlickLing Components and Technology Used FlickLing search engine consists of two basic components e the graphical user interface which controls the search engine features queries ranking of results etc functionalities related to cross linguality translations suggestions related term etc and the game like features of the task flow of images users ranking etc e a set of web services working behind that are in charge of accessing Flickr managing the system s databases and generating user logs For the development of FlickLing only free software tools have been used The user interface is implemented entirely in Java and Google Web Toolkit GWT GWT is an open source Java development framework for creating AJAX based interfaces It is a web development technique for creating interactive Web applications using HTML Javascript CSS and XML web applications GWT provides many functionalities tools and performance improvements that are difficult to manage when developing at a
10. arch becomes a bilingual or monolingual problem for the user The rest of hints up to five are always keywords to find the target image see Figure 9 This hint mechanism was introduced after initial testing of the task to avoid making the task too difficult to engage potential users monolingual multilingual water building Search English water building Spanish agua edificio Dutch e I write in English v write a translation Figure 4 Multilingual Interface manipulating translation suggestions in the personal dictionary Find this image 7 monolingual multilingual river cloudy sky Search English river cloudy sky Spanish r o add cielo Dutch rivier vaag hemel I write in trans ate English v eer Ena soa Write your translation of the term Search results 1 20 of 500 for river cloudy sky Figure 5 Multilingual Interface adding new translations to personal dictionary You also might want to try with california beach losangeles ocean angeles santamonica venice usa sunset Santa Monica Pier ocean california longexposure sunset water oregon portland pier santamonica stock show all Santa Monica Pier ocean santa people beach wheel coast pier waves santamonica monica show all Santa Monica Pier Santa Monica Pier Redux pier losangeles santamonica july southerncalifornia san
11. ask Therefore some restrictions were observed when designing the interface i all standard multilingual search facilities should be present ii non standard or overly innovative interface aspects should be avoided to avoid testing a particular approach to multilingual search interfaces rather than a general study of users behaviour when searching multilingual information iii as we were seeking for spontaneous non controlled users versus controlled populations under laboratory conditions the interface should be intuitive and usable without pre search training iv Flickling should work robustly at least with the two main web browsers IE and Firefox In the remainder of this section we focus on the interface functionalities of Flickling that follow the above requisites 2 1 Search Modes The search engine has two search modes e A standard search mode with no translation facilities as shown in Figure 1 e A multi language interface which automatically translates query terms into the target lan guages enabled by the user as shown in Figure 2 It also shows translation suggestions and allows the user to add and remove query terms In this multilingual interface the user selects the source language she s writing in his pre ferred language by default and the languages in which she wishes to translate her query all target languages by default The user can enable or disable individual target languages just by clicking on them
12. dent search carried out to check that the images were not too hard to find This requisite proved hard to meet because it was highly dependent from the source target language combination Some images were easy to find in a monolingual setting but hard to retrieve in a cross language setting A difficulty when selecting images was the large size of the Flickr database Even using the right keywords some images might be buried in the ranking simply because there were lots of similar images A strategy to alleviate this problem was to search images by combining pairs of common tags which were not likely to appear simultaneously in the same image such as phone cow This method was rather successful and in general once the user finds the appropriate keywords the image tends to be in the first ten positions of the ranking 5 User Logs iCLEF participants could participate in the track doing basically two things a interactive ex periments recruiting their own set of users and b search log analysis and data mining using the Flickling log file distributed by the organisation In both cases search logs are the essential source of information Therefore how search logs are recorded is an essential part of the Flickling interface Each log line corresponds to a unique functionality even though each interaction may generate more than one log line as the examples below will show Log lines have five different fields separated by the pipeline symbo
13. erview of iCLEF 2008 search log analysis for Multilingual Image Retrieval In Borri F Nardi A and Peters C CLEF 2008 Workshop Notes
14. good indicator of an extensive experience using FlickLing e clear e easy e familiar e interesting e relevant to you 4 Did you find multilingual search capabilities useful to find images in Flickr 5 Would you now prefer to use a multilingual search facility for your own image searches 6 Which in your opinion are the most challenging aspects of the task e Selecting finding appropriate translations for the terms in my query e Handling multiple target languages at the same time e Finding the target image in very large sets of results 7 Which interface facilities did you find most useful e The automatic translation of query terms e The possibility of improving the translations chosen by the system e The additional query terms suggested by the system You might also want to try with e The assistant to select new query terms from the set of results 8 Which interface facilities did you miss e Detection and translation of multi word expressions Bilingual dictionaries with a better coverage A system able to select the translations for my query terms better e More support to decide what the possible translations mean and therefore which ones are really appropriate e The possibility to search according to visual features of the images search images that look like this search only B W images search only for dark images e The classification of search results in different tabs according to the image c
15. jDh5AF2JXi0515 giveUp photo 7983304 at 104 460667133 secs Tue May 20 15 49 47 2008 user_2 NjDh5AF2JXi0515 giveUp score updated 8 0 P 0 0 T 0 0 The user fills in the questionnaire after giving up Each question has a numeric identifier Tue May 20 15 49 47 2008 user 2 NjDh5AF2JXi0515 loglgiveUpQuestionnaire 0 false 1 false 2 false 3 false 4 false 5 true comments I can t recognize the animal in the image because the thumb is to small and or I m so bad in biology For a more comprehensive description of the user logs generated by FlickLing and the mappings of the questionnaires and language identifiers see the help file distributed among the iCLEF participants 6 Questionnaires After either finding or giving up on a target image the user is asked to fill in a small post image questionnaire with questions about her impressions about the task performed see Figure 10 The questionnaire after finding an image is the following 1 OY wie te SD It was easy It was hard because of the size of the image set It was hard because the translations were bad It was difficult to describe the image It was hard because I didn t know the language in which the image was annotated It was hard because of the number of potential target languages 5 The help file is available at http nlp uned es iCLEF 2008 iclef logs help txt Please fill in this form Why are you giving up on this image There are too many images fo
16. l ASCII time username session ID method functionality message returned or additional information Some examples illustrating the logs are the following 1 Successful registration Tue May 20 15 41 54 2008 user_2 NjDh5AF2JXi0515 register succes 2 Successful login Tue May 20 15 41 56 2008 user 2 login2 success 3 A new search session is created and a new target image is assigned Tue May 20 15 41 56 2008 user_2 NjDh5AF2JXi0515 getTargetImg new ActiveSearch created photoid 7983304 Tue May 20 15 41 56 2008 user_2 NjDh5AF2JXi0515 getTargetImg success photoid 7983304 4 A monolingual search in launched and retrieved from the system s cache Note that time is stopped while querying the database Tue May 20 15 41 59 2008 user_12 u8ygLdcq7yGK121 search launch query big ben 100 20 Tue May 20 15 41 59 2008 user_12 u8ygLdcq7yGK121 pauseTime time set on pause Tue May 20 15 41 59 2008 user 12 u8ygLdcq7yGKi21 search 500 results retrieved from QueryCache Tue May 20 15 42 00 2008 u8ygLdcq7yGK121 playTime time set on play mode 5 A cross language search from Spanish into other available languages each language is de noted by a number is launched and retrieved from Flickr s database Again time is stopped while querying Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M pauseTime time set on pause Tue May 20 15 45 54 2008 user_1 s51DItDdyW81j2M clsearch launch query saltando naranja 0 20 Tue May 20 15 45 54 2008 user_1 s51
17. lower level The Flickling GUI has made extensive use of features like application localisation history management and asynchronous remote procedure calls to name a few In order to extend the graphical capabilities of GWT we used the GWT Ext library On the other hand FlickLing web services are implemented in Python using the TurboGears web application framework The communication with Flickr is rather simple FlickLing only interacts with Flickr in order to launch queries and retrieved results and it is established through the Beej s Python Flickr API The system s databases are structured as MySQL tables and they store users information e g registration information language skills target images shown score etc the system cache e g queries launched to Flickr and their associated relevant results image descriptions etc dictionaries and the pool of target images Finally data interchange between the user interface and the web services is performed through JSON objects 8 Conclusions In this paper we have presented FlickLing a search interface for Flickr designed and implemented by the NLP amp IR Group at UNED to support the CLEF 2008 interactive task 1 The interface allows users to search Flickr images in six language simultaneously offering automatic query trans lation and support for interactive query translation and refinement Flickling features multilingual image search as a competitive online game where a
18. ned to allow for studies which focus on specific user profiles and also to engage users in group oriented competition The list of groups is predefined and everyone wanting to create a new group must submit a request to the Flickling system manager At any point during a session a user may see his personal scores points average precision average time spent per image etc and compare them with all other users A similar rank is also maintained for groups 3 Translations and Dictionary Managing 3 1 Dictionaries FlickLing handles translations in up to six languages Dutch English French German Italian and Spanish We built our dictionaries from the freely available XDXF Dictionaries The sources required some simple normalisation and symmetrisation before building the translation tables XDXF Dictionaries were chosen because in spite of their poor quality in some domains they were general purposes dictionaries and offered a reasonable coverage between the six languages considered in FlickLing EN ES DE NL IT ES 3http xdxf revdanica com down Since we didn t have linguistic tools for all languages involved we decided to match query terms with dictionary entries using stemming Each dictionary entry was stemmed using a Snowball implementation This decision have obvious pros and cons inflected terms can be translated without the need for lemmatisers but occasionally the dictionary happens to group translations from diffe
19. nformation Systems Applications H 4 m Miscellaneous General Terms interactive information retrieval cross language information retrieval Keywords iCLEF Flickr log analysis multilingual image search user studies 1 Introduction This paper presents FlickLing a multilingual search interface for Flickr designed and implemented by the UNED NLP amp IR Group nlp uned es for the CLEF 2008 interactive task 1 Department of Computer Science University of Sheffield Regent Court 211 Portobello Street Sheffield S1 4DP UK lFlickLing is available at http soporte1 1si uned es flickling Flickr is a popular online community where users share and organise their personal image collections annotated with titles descriptions and tagged with terms freely chosen by users folk sonomies According to Wikipedia as of November 2007 it already claimed to host more than 2 billion images Flickling was designed to collect a large search log of multilingual image searches which serves as the input data for the log analysis shared task at iCLEF 2008 FlickLing consists of two search modes mono and multilingual which allow to retrieve Flickr images annotated annotated in different languages From a given query FlickLing is able to automatically translate it into several languages remembering the user s preferred term translations and offer the user mechanisms to refine the query and improve the translations provided by the system
20. noxii naumachiae domiciano javec sarlosquevamosamorirtesaludamos ocultar una parte La arena era un valo de 75 por 44 metros y en realidad era una plataforma construida en madera y cubierta de arena Todo el subsuelo era un complejo de t neles y mazmorras el hipogeo en el que se alojaba a los gladiadores a los condenados y a los animales El suelo dispon a de varias trampillas y montacargas que se conectaban con el s tano y que pod an ser usadas durante el espect culo Colosseo Roma Italia Figure 8 The document icon allows to access the image description The image is described in English I want to give up anyway Sr Figure 9 The first hint provided by the system is always the annotation language of the target image 2 3 User profiling and interface localisation All Flickling users register before starting their searches This is needed to track the game like features of the interface scores images already seen etc and also to enrich the search logs user s language abilities search history etc The user profile focuses on language abilities and records native language s preferred interface language and skills in each of the task languages active knowledge passive knowledge or unknown The interface has been localised in the six languages handled by the multilingual search facility EN ES IT FR NL DE In addition users may register as belonging to a certain group this is desig
21. o their images Therefore Flickr related terms often suggest translations for the query terms even if Flickr does not explicitly support cross language suggestions When a potential translation for a query term appears in Flickr suggested terms this is a good indicator that it is a good translation in the context of the query 3 The preferences of the user s personal dictionary If the user has previously selected a dictionary translation for a given term or added a new translation this is taken as evidence in favour of such translation This is a non contextual hint because the user might have manipulated the term translations in a different search scenario i e with a different query context The best candidate is chosen by the multilingual interface as preferred translation while the others are shown if requested as translation suggestions see Figure 4 for a graphical example 4 Image set Around 100 images were selected as the target for the Flickling game there were shown to every user in a randomised order We researched for images in the six languages of the interface although the final set of images is not totally balanced because frequently images annotated in languages other than English also contained some descriptors in English In the final set approximately 6096 of the images has some English descriptor Fortunately this had only a relative impact on the multilingual search of the task first because the target language
22. r my search The translations provided by the system are not right can t find suitable keywords for this image Ihave difficulties with the search interface ljustdon t know what else to do Additional comments The image is hard to describe T Figure 10 Post image questionnaire after giving up It was hard because I needed to translate the query If the user gives up before finding the image the questionnaire is then 1 gs wm ges e There are too many images for my search The translations provided by the system are not right I can t find suitable keywords for this image I have difficulties with the search interface I just don t know what else to do Additional comments Lastly regardless the results of her searches after searching 15 images the user was shown 6 a final questionnaire In this case the questionnaire asks the user to describe her overall experience giving details about her behaviour the most challenging aspects of the task the prob lems found and her opinions about the interface functionalities to name a few The complete questionnaire is the following 1 2 3 Do you need to search information in foreign languages in your daily life Do you often use image search facilities The search task you performed was 6 After this final questionnaire the user can continue playing at will We established this threshold after the 15th search session as a
23. rent words under the same entry This adds semantic ambiguity that can eventually be fixed via user s manual intervention 3 2 Term to term translation strategy Once our dictionaries are built FlickLing automatic translation provides a term to term trans lation From a given query the system performs a simple tokenisation using blank spaces and punctuation as token limits and each token is stemmed just as with the dictionary entries see Section 5 for examples on each of these steps The translation strategy was a delicate issue Search is performed via the Flickr API which per mits full boolean queries but does not support term weighting or synonym operators The best op tion is then launching the boolean query termi OR termitranslationi OR termitranslation2 OR AND term2 OR term2translation1 OR term2translation2 OR AND In this situation retaining all translations as many effective cross language IR systems do is not a reasonable strategy Therefore we decided to filter translations using two criteria one is query independent and the other one takes the query context into account The system orders the candidates according to 1 The edition distance between the term and the translation candidate which is a useful heuristic in many practical situations 2 The matching with the related terms provided by Flickr This proved to be a very useful heuristic because many Flickr users add tags in more than one language t
24. see Figure 3 Flickr is available at http www flickr com Find this image monolingual multilingual river bridge Search Search results 1 20 of 34 for dfdfd Figure 1 FlickLing Monolingual Interface monolingual multilingual river bridge clowd Search English river bridge clowd German fluss br cke add Spanish r o puente add French rivi re pont add Italian fiume ponte add Dutch rivier brug add I write in translate my query into English v Ger Eng Spa Fre Ita Dut Figure 2 FlickLing Multilingual Interface Find this image monolingual multilingual river bridge Search English river bridge Spanish r o puente Dutch rivier brug I write in translate my query into English v Ger Eng Spa Fre Ha Dut Search results 1 20 of 500 for river bridge Figure 3 Multilingual Interface selecting source and target languages The user can personalise her own dictionary by using two different functionalities First the user can modify the choice of term translations initially made by the system see Figure 4 Every click to enable or disable a suggested translation gives respectively a positive or negative score to each translation These scores associated to each possible translation are used to sort the possible translations according to the user s preferences as explained in Section 3 Second the user can
25. tamonicapier 2007 Santa Monica Pier california santa people beach water la pier losangeles los angeles show all Santa Monica Pier Figure 6 Ranking of results Search results 1 20 of 500 for santa monica pier You also might want to try with california beach losangeles ocean angeles santamonica venice usa sunset vacation west promenade water beach ocean sea sunset brighton california sky england seaside waves uk SUPR summer light pacific lake silhouette florida surf orange sanfrancisco people shore navy chicago nikon canon blackandwhite ship reflections dusk white landscape westpier cloud jetty hide some Santa Monica Pier ocean california longexposure sunset water oregon portland pler santamonica stock show all Search for sunset Add sunset to your query and search Santa Monica Pier ocean santa people beach wheel coast pier waves santamonica monica show all Figure 7 Related terms and image tags can be used to refine or launch new queries Hipogeo Colosseo di Roma italy rome roma italia amphitheatre colosseum coliseo edgar flavio tito coliseum gonzalez colosseo anfiteatro flavian vespasiano flavianamphitheatre anfiteatroflavio flavium amphitheatrumflavium amphitheatrum ner n afuoco hipogeo wowiekazowie edgargonz lez fotoguia
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