Why does search engines like Google fails on "shirt without stripes"?

Β· 390 words Β· 2 minute read

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Why does search engines like Google fails on “shirt without stripes”?

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Search engines like Google rely on algorithms to match user queries with relevant web pages. In the case of the query “shirt without stripes,” the search engine may struggle to understand the user’s intent because the query is quite vague.

Without additional context or qualifiers, the search engine has to guess at what the user is looking for. It may interpret the query as a request for pages about shirts that don’t have any stripes at all, or it may assume that the user is looking for shirts with patterns other than stripes.

The search engine may also struggle to find relevant pages because the query contains a negation (“without”). Search engines are optimized to match positive queries, which ask for something specific rather than ruling something out.

To improve the search results for this query, users can try to add additional keywords or qualifiers to provide more context. For example, they could try searching for “solid color shirts” or “shirts with no stripes.” Additionally, search engines are constantly improving their algorithms, so it’s possible that the search results for this query may improve over time.

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So a negation is bad technique for search queries?

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Negations can be a challenging technique for search queries because search engines are generally designed to look for positive signals, rather than negative ones. That is, they are better at identifying content that matches the user’s search criteria than they are at filtering out content that doesn’t match.

When a user includes a negation in their search query, such as “shirt without stripes” or “car rental not in London,” the search engine must identify pages that don’t contain the specified term or phrase. However, it can be difficult for the search engine to determine whether a page is relevant to the query if it simply lacks a specific feature or term.

As a result, negations can sometimes lead to inaccurate or irrelevant search results. To improve the accuracy of search results, users can try to include more specific and relevant terms in their queries, rather than relying solely on negations. Additionally, search engines are constantly improving their algorithms to better understand the intent behind user queries, which may help to address some of the challenges associated with negations in search.