Artificial intelligence applications can be used in scientific information retrieval at various stages. It is particularly suitable for the planning phase of information retrieval and for actual search in occasions that require only a small number of references. AI has also been integrated into many existing information retrieval tools.
At least for now, AI cannot generate extensive searches from diverse sources with comprehensive coverage of references. The answers produced by AI must always be checked by yourself, as is often the case with other uses of AI too.
Prompt and discuss:
Utilize the conversation option of AI applications in your information search. You can ask follow-up questions to the application either on your own or by choosing from ready-made questions. Through conversation, you often get more precise answers and a better overall understanding of the topic. Test various terms in your prompts and try different conversation starters.
Follow the rules:
It is important to follow the guidelines provided for AI use in studies and research. If the use of AI is permitted, it is generally recommended to indicate how it has been used in the work. Check out UEF's general guidelines on the use of AI.
Remember data security! Do not provide personal or confidential information to AI. See the UEF guidelines for more information.
Information retrieval from scientific databases
Traditional literature reference databases have been enhanced with AI tools. In the Web of Science database the tool is called Research Assistant, and in the Scopus database it is called Scopus AI.
These database tools utilize both external language models and their own technologies.
The two tools have similarities:
- Search is done in natural language.
- Search can be performed in different languages.
- The search is first translated into English using AI, so it is advisable to check the translation.
- Follow-up questions are in the same language as the original question.
- The program retrieves a couple of suitable sources from the database's own materials and uses them to create an answer to the question.
- The answer includes references to the sources used.
- The program presents a concept map on the topic and indicates top researchers and the most cited articles of the topic.
- The search can be continued with ready-made, often more elaborating questions.
The data entered into the program is not stored in the system, but can be used to enhance the program. Therefore, data security is worth remembering in this program as well.
Searching
The program first formulates a natural language question in English from the user’s prompt and then usually converts the question into a search query. The query includes alternative terms.
The search query is visible to the user, so they can check if the key terms are included.
Summaries
The answer is based on Scopus materials from 2003 onward. Scopus uses around ten sources, sometimes fewer. The selection of sources is particularly based on the text of the abstracts.
The answer includes actually two different summaries. The other, called expanded summary, gives a more detailed answer, and uses more sources, up to 20.
Regardless of the original question’s language, the answer is in English.
Additional Information
The concept map provides detailed information on individual concepts related to the topic. The description of a concept includes references to sources.
The program identifies three key researchers in the field based on their research interest and the number of articles and citations.
The program lists key publications related to the topic, which are selected based on citation counts. These publications can be older than 2003.
Saving Searches
Searches cannot be re-run during the session, nor can they be saved for later use.
Read more about program’s operating principles and data security.
Read detailed description about responses produced by the program.
The program does not share data with third parties and does not use it to train the model. However, data security is worth remembering in this program as well.
Searching
The search can be started with a direct question. Another way is to conduct a more guided search, which has three starting points, and each one’s answer is slightly different. A topic search emphasizes understanding a specific issue. A literature review highlights the sources found. A journal search helps identify key journals on the topic, not individual articles.
The program performs a simple search using the key terms of the question. The number of results tends to be large, since the program does not search all the terms together, but each of them separately (as connected with OR-operator).
The prompted question can be phrased to look for certain types of publications, such as the latest or the most cited articles.
Summaries
The answer is based on the entire Web of Science Core Collection. If you want to emphasize newer sources, it is advisable to mention in the question “… based on recent documents …”. Total of eight sources are used to compile the answer. In addition to the actual sources used, you can view the entire original search result list. The search query used to retrieve the results is stated at the beginning of the list.
The answer to the question is given in the same language as the original question.
Additional Information
More detailed information is given on the main topic derived from the subject - not precisely related to the original question itself.
The concept map lists individual concepts related to the main topic. Links of the map provide a ready-made, usually very long list of sources related to each concept.
The most cited researchers are outlined briefly. In addition, it is possible to examine how much has been published on the topic in the course of time.
Saving Searches
Research Assistant shows all searches made during the session, and you can go back to review them. If you have a Web of Science account, you can also save searches for later use.
Watch a demonstration and instructions of the program.
Read more about program’s operating principles and see more examples of search questions.
Other AI applications for different stages of information retrieval
Primarily, it is recommended to use AI applications acquired by UEF, the provider of which has an agreement on the processing of personal data.
Along with Scopus and Web of Science AI tools, such a suitable application is Microsoft Copilot Enterprise, which needs to be logged in through your UEF Microsoft account. See instructions on the UEF guidelines mentioned above.
With the help of AI-generated answers, you can quickly familiarize yourself with a new topic: what it is about, what kind of aspects are involved. AI is also a good tool in defining concepts. Read more about exploring the topic and concepts (without AI) in the Guide to Information Retrieval.
You can proceed in two ways. In both cases, be prepared for the possibility that AI may “hallucinate,” i.e., produce inaccurate text.
1. Start by asking AI about the topic. The answer will help you get an idea of what the topic includes and where to head your information retrieval. Note that if the topic is completely unfamiliar to you, it is difficult to assess the accuracy of the AI-generated answer. Therefore, verify the information from proper scientific sources.
Examples of how to start conversation:
- “What means microaggression?”
- “What kind of actions can be done to prevent eutrophication of waters?”
2. Familiarize yourself with the topic elsewhere first, for example, by reading research literature, and then ask AI for more specific questions. When you are already more familiar with the topic, you will be better able to assess the accuracy of the answers. You can also get more precise or more relevant answers when you include concepts and terminology that accurately describe your research topic in the prompt.
Examples of how to start conversation:
- “How can teachers promote a positive climate at elementary schools through inclusive classroom activities?”
- “I'm in the process of brainstorming the subject of my thesis. I am familiar with Lev Vygotsky's theory of the zone of proximal development through research literature. In my thesis, I want to compare Vygotsky's theory to some other theory of learning. List five learning theories that I can possibly use as a reference in my thesis.”
Examples of suitable AI applications:
- Copilot (Microsoft) – recommended
- ChatGPT 4o-versions (OpenAI)
- Gemini (Google)
Keywords:
AI applications are already quite good at suggesting keywords for information retrieval, especially in English. Applications are capable of finding word equivalents and synonyms in different languages.
However, they are not very good at formulating keywords in such a way that they work effectively when searching for information in databases specialized in scientific publications. Typically, the application presents rather long expressions, for example, ‘dietary effects on gut microbial diversity’ or ‘the importance of sleep for memory function’. These need to be broken down into simple, separate terms, e.g., ‘diet - gut microbes - diversity’ or ‘sleep - memory’.
Keyword lists are rarely comprehensive, at least not on the first try. You can ask the application to provide more terms and refer to the types of words you wish for. You can request plenty of keywords, from which you can choose the best ones. To get a more comprehensive view, you can try multiple AI applications.
Queries:
The best AI applications are also able to formulate ready-made search queries for databases: keywords are combined with operators and phrases are marked properly. However, word truncation is usually lacking and the formulation of individual keywords is unfinished.
Always evaluate yourself which keywords are actually useful for your topic. Also, check the logic and functionality of the search query. In the picture you see a correct query model and points to pay attention to.
Examples of how to start conversation:
- “Can you find synonyms for the term sensory defensiveness?”
- “Tell me keywords for information search about the topic how the use of wood affects fine particle emissions.”
- “If there are two main concepts: environmental effects and vehicles, can you give me synonyms and related search terms for these both in a table form, where concepts are in columns.”
- “Use Boolean logic to find publications about eating disorders and young people. Use several synonyms for both concepts.”
Examples of suitable AI applications:
Copilot (Microsoft) – recommended
ChatGPT 4o-versions (OpenAI)
Gemini (Google)
Perplexity
FintoAI is an application specializing in keywords. It suggests words based on YSO thesaurus in Finnish, Swedish or English. FintoAI is given a text as input, e.g. a summary describing the topic.
When searching for information, it is advisable to first distinguish between applications that do not search for information themselves but base their entire response on a generative language model, i.e., simply on the probabilities of word occurrences. An example of this is the basic version of ChatGPT, first published in 2022, which is neither a database nor a search engine.
Many other applications utilizing language models perform the task using genuine sources:
Applications utilizing generative language models
Choose an application, where genuine information retrieval is done from real sources. The application uses these to generate an answer. Depending on the application, the search can go through the open web sources (e.g. Copilot and ChatGPT 4o) or a specific database containing selected information, such as open access scientific articles (e.g. Elicit). The result of the search is a short answer to the question or a summary of the topic, along with the sources used in the answer.
Formulate the question clearly but concisely and include sufficiently precise terms to get a relevant answer. Partition a complex task into smaller parts.
The answer produced by AI is often based on a very small number of documents. There is little information on how the application selects the sources it uses, which undermines the reliability of the answer. Therefore, check the original sources which the AI refers to. Also, do your own search from other sources to get a more complete picture.
Note that AI does not always act the way it is asked of. For example, even if you ask the AI application to base its response only on scientific or peer-reviewed articles, it may not necessarily do so.
Examples of how to start conversation:
- “What are the key challenges in addressing environmental exposure in the Global South?”
- “What is the role of internal communication in organization change, based by articles in peer-reviewed journals?”
- “I am writing an academic essay about eating disorders in young adults and supporting the healing process. Could you suggest academic articles? Try to find peer-reviewed publications.”
Examples of suitable AI applications:
- Copilot (Microsoft) – recommended
- ChatGPT 4o-versions (OpenAI)
- Elicit
AI is used in search engines in ways other than based on generative language models, too:
Applications structuring and visualizing search results
In these search engines, information retrieval is proceeded in the traditional way, with search queries. The mentioned database contains open access scientific publications, such as articles, making it reliable source of information. The application uses AI to group the search results, making it easier to evaluate the themes related to the topic. The result of the search is a list of references.
Example of a suitable application:
- Open Knowledge Maps
Search by existing article
Some applications use an existing text or document suitable for the topic, such as an article or an abstract, as a starting point. The application analyses the text and searches for similar references. The result of the search is thus a list of references.
Examples of suitable applications:
- Connected Papers
- Elicit
- Keenious
- Research Rabbit
Many traditional databases (e.g., Scopus, Web of Science) contain a similar function that suggests further references based on the selected article.
Different referencing styles have their own general rules how to cite AI. E.g. APA style for ChatGPT in-text citation is: (Open AI, 2024) and reference list entry:
Open AI (2024). ChatGPT (May 13 version) [Large language model]. https://chat.openai.com/chat.
Read more:
How to cite ChatGPT? (APA)
How do I cite generative AI in MLA style?
The Chicago Manual Style / Q&A
Nevertheless, always follow the guidelines of your own discipline or publisher regarding the use and reporting of AI and citing to it.
Limitations of AI in information retrieval
Restricted sources:
When using an AI application that genuinely retrieves existing sources, the answer produced by AI is often based on a very small number of documents. There is little information on how the application selects the sources it uses, which weakens the reliability of the answer. AI applications can reach only open access materials. Some of the most relevant sources may be missing altogether. Therefore, check the original sources to which the AI refers. Also, conduct your own search in actual scientific databases to get a more comprehensive view.
The quality of results may vary:
AI applications, including those using genuine publications as sources, can produce incorrect or biased responses. The answer is also not always exactly the same, even if you ask the same question.
User accounts and charges:
Many AI applications can be used for free, but their capacity and features are limited. Payments provide more services. Even free versions often require the creation a user account.
Privacy:
From a privacy perspective, there may be problems with the use of AI applications. Applications can store personal information and conversations, which can be used for the tool’s own purposes and possibly transferred further.
Copyright:
AI-generated outputs do not have copyright. Instead, the AI application itself may infringe copyright when using material found online without permission. An AI application that cites its sources is a safer choice in terms of copyright.
Page last updated: 30.9.2024.