Wikipedia Retrieval

In 2010, ImageCLEF's Wikipedia Retrieval used a new collection of over 237,000 Wikipedia images that cover diverse topics of interest. These images are associated with unstructured and noisy textual annotations in English, French, and German.

This is an ad-hoc image retrieval task; the evaluation scenario is thereby similar to the classic TREC ad-hoc retrieval task and the ImageCLEF photo retrieval task: simulation of the situation in which a system knows the set of documents to be searched, but cannot anticipate the particular topic that will be investigated (i.e. topics are not known to the system in advance). The goal of the simulation is: given a textual query (and/or sample images) describing a user's (multimedia) information need, find as many relevant images as possible from the Wikipedia image collection.

Any method can be used to retrieve relevant documents. We encourage the use of both concept-based and content-based retrieval methods and, in particular, multi modal and - new this year - multi lingual approaches that investigate the combination of evidence from different modalities and language resources.

-English only: 70,127

-German only: 50,291

-French only: 28,461

-English and German: 26,880

-English and French: 20,747

-German and French: 9,646

-English, German and French: 22,899

-Language undetermined: 8,144

-No textual annotation: 239

The main difference between the ImageCLEF 2010 Wikipedia collection and the INEX MM collection (Westerveld and van Zwol, 2007) used in the previous WikipediaMM tasks is that the multilingual aspect has been reinforced and both mono- and cross-lingual evaluations can be carried out. Another difference is that this year, participants will receive for each image both its user-provided annotation and also links to the article(s) which contain the image. Finally, in order to encourage multi modal approaches, three types of low-level image features were extracted using PIRIA, CEA LIST's image indexing tool (Joint et al., 2004) and are provided to all participants.

(Joint et al., 2004) M. Joint, P.-A. Moëllic, P. Hède, P. Adam. PIRIA: a general tool for indexing, search and retrieval of multimedia content In Proceedings of SPIE, 2004.


(Westerveld and van Zwol, 2007) T. Westerveld and R. van Zwol. The INEX 2006 Multimedia Track. In N. Fuhr, M. Lalmas, and A. Trotman, editors, Advances in XML Information Retrieval:Fifth International Workshop of the Initiative for the Evaluation of XML Retrieval, INEX 2006, Lecture Notes in Computer Science/Lecture Notes in Artificial Intelligence (LNCS/LNAI). Springer-Verlag, 2007.

Search Engine: Cross-Modal Search Engine (CMSE by UniGe) that allows you to search the ImageCLEF 2010 Wikipedia image collection through a web interface using text queries, example images or both at once.

• how well do the retrieval approaches cope with larger scale image collections?
• how well do the retrieval approaches cope with noisy and unstructured textual annotations?
• how well do the content-based retrieval approaches cope with images that cover diverse topics and are of varying quality?
• how well can systems exploit and combine different modalities given a user's multimedia information need? Can they outperform mono modal approaches like query-by-text, query-by-concept or query-by-image?
• how well can systems exploit the multiple language resources? Can they outperform mono-lingual approaches that use for example only the English text annotations?

In the context of INEX MM 2006-2007, mainly text-based retrieval approaches have been examined. Here, we hope to attract more visually-oriented approaches and most importantly, multi modal and multi lingual approaches that investigate the combination of evidence from different modalities and languages. The results of WikipediaMM at ImageCLEF 2008/2009 showed that multimedia retrieval approaches outperformed for certain topics the text-based approaches, but globally the retrieval based on text remains unbeaten. The retrieval of multimedia documents will stay in the focus of attention for 2010. This year, a second focus will be the effectiveness of multi lingual approaches for multimedia document retrieval.

The topics for ImageCLEF 2010 Wikipedia Retrieval task include (i) topics based on analysis of a search engine's logs, and (ii) topics used in previous years.

DOWNLOAD (participants only)

The 2010 topics:

• The topics (title + example images) can be downloaded HERE.
• The topics (title + example images) together with the narratives used by the assessors to perform the relevance assessments can be downloaded HERE.
• The example images in the topics can be downloaded HERE; these images are not part of the collection and are distributed under the creative commons licence.
• The low-level visual features of the example images can be downloaded HERE; the features and the file format are the same as the ones used for the images in the collection.
• The relevance assessments (qrels) for the Wikipedia Retrieval 2010 topics can be found here.

The topics are multimedia queries that can consist of a textual and a visual part. Concepts that might be needed to constrain the results should be added to the title field. An example topic in the appropriate format is the following:

<topic>

  <number> 1 </number>

  <title xml:lang="en">historic castle <title>

  <title xml:lang="de">historisches schloss<title>

  <title xml:lang="fr">château fort historique<title>

  <image> castle.jpg </image>

</topic>

Therefore, the topics include the following fields:

• title: query by keywords in each of the 3 languages (English, French, German)
• image query by one or more images
• narrative description of the information need where the definitive definition of relevance and irrelevance are given; this will be provided during the assessment phase.

Experiments are performed as follows: the participants are given topics, these are used to create a query which is used to perform retrieval on the image collection. This process iterates (e.g. maybe involving relevance feedback) until they are satisfied with their runs. Participants might try different methods to increase the number of relevant in the top N rank positions (e.g., query expansion).

Participants are free to experiment with whatever methods they wish for image retrieval, e.g., query expansion based on thesaurus lookup or relevance feedback, indexing and retrieval on only part of the image caption, different models of retrieval, and combining text and content-based methods for retrieval. Given the many different possible approaches which could be used to perform the ad-hoc retrieval, rather than list all of these we ask participants to indicate which of the following applies to each of their runs (we consider these the "main" dimensions which define the query for this ad-hoc task):

Annotation language:
Used to specify the target language (i.e., the annotation set) used for the run: English (EN), German (DE), French (FR) and their combinations.

Comment:
Used to specify whether the <comment> field in the text annotation has been used: Yes/No.

Topic language:
Used to specify the query language used in the run: English (EN), German (DE), French (FR) and their combinations.

Run type:
We distinguish between manual (MAN) and automatic (AUTO) submissions. Automatic runs will involve no user interaction; whereby manual runs are those in which a human has been involved in query construction and the iterative retrieval process, e.g. manual relevance feedback is performed. A nice description on the differences between these types of runs is provided by TRECVID at here

Feedback or Query Expansion:
Used to specify whether the run involves query expansion (QE) or feedback (FB) techniques, both of them (QEFB) or none of them (NOFB).

Retrieval type (Modality):
This describes the use of visual (image) or text features in your submission. A text-only run will have modality textual (TXT) and a purely visual run will have modality visual (IMG). Combined submissions (e.g., an initial text search followed by a possibly combined visual search) will have as modality: text+visual (TXTIMG), also referred to as "mixed".

Topic field:
This specifies the topic fields employed in the run: only the title field of the topic (TITLE); only the example images in the topic (IMG_Q); both the title and image fields (TITLEIMG_Q).

Participants can submit up to 20 system runs. The submission system is now open at the ImageCLEF registration system (select Runs > Submit a Run).

Participants are required to submit ranked lists of (up to) the top 1000 images ranked in descending order of similarity (i.e. the highest nearer the top of the list). The format of submissions for this ad-hoc task is the TREC format. It can be found here.

Please note that there should be at least 1 document entry in your results for each topic (i.e. if your system returns no results for a query then insert a dummy entry, e.g. 25 1 16019 0 4238 xyzT10af5 ). The reason for this is to make sure that all systems are compared with the same number of topics and relevant documents. Submissions not following the required format will not be evaluated.

Information to be provided during submission

• Method Description: A brief description of the approach employed in the submitted run.
• Retrieval type: The modality of the employed features: textual, visual, or a combination of both (mixed).
• Language: The annotation language(s) used: "English", "French", "German", "English & French", "English & German", "French & German", "English, French & German".
• Run type: Select either Automatic or Manual. Whether the run includes the use of relevance feedback should be specified below.
• Primary Run: Indicate whether this is the group's primary run.
• Other information: Specify the remaining aspects of the submitted run by deleting as appropriate:
  
  

  Topic language: EN, DE, FR, EN+DE, EN+FR, FR+DE, EN+FR+DE
  
  Comment used: YES, NO
  
  Feedback/expansion : FB, QE, FBQE, NOFB
  
  Topic field: TITLE, IMG_Q, TITLEIMG_Q
  
  
  

• Additional resources used: Optional field to describe any additional resources employed.

Both Notebook papers and Book of Abstracts were assigned an ISBN number (978-88-904810-0-0). The papers are also indexed by DBLP.

• 15.2.2010: registration opens for all ImageCLEF tasks
• 30.3.2010: data release (images + metadata + article)
• 6.5.2010: topic release
• 15.5.2010: registration closes for all ImageCLEF tasks
• 20.6.2010: submission of runs
• 23.7.2010: release of results
• 15.8.2010: submission of working notes papers
• 20.09.2010-23.09.2010: CLEF 2010 Conference, Padova, Italy

• Jana Kludas, Computer Vision and Multimedia Laboratory, University of Geneva, Switzerland, Jana.Kludas@unige.ch
• Adrian Popescu, TELECOM Bretagne, France, popescu_adi@yahoo.co.uk
• Theodora Tsikrika, Interactive Information Access Group, CWI, Amsterdam, The Netherlands, theodora.tsikrika@acm.org