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A competitive market is pushing site search technology to new plateaus
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S.L.I. offers its products on a hosted basis as does Logika. Logika sells a spider-based site search product that crawls retailers’ data, then presents search results and categorization. “Our spider is specifically designed to follow the dynamic content and then create a robust index of just that site,” says John Sortino, vice president of sales and marketing. Depending on contracted frequency, the spider re-crawls the site daily, weekly or monthly. As an indication of the competitiveness of the marketplace, both S.L.I. and Logika offer free tests to prospective customers.
As the proliferation of vendors indicates, retailers are understanding the importance of search and many are dong something about it. “This is a very interesting market for search vendors,” says Manning. “Retailers are looking to upgrade to the right search engine. They’re coming to the realization that if they’re online retailers, they are underselling if they’re not using the right search technology.”
And that means what?
Don’t be daunted by search vendors’ terminology, says Forrester Research. To help, Forrester offers the following definitions:
Boolean Retrieves documents based on the number of times keywords appear in the text. Using AND, OR and NOT makes queries more specific.
Clustering Dynamically creates groups (“clusters”) of documents based on similarity, usually based on statistical analysis of the contents and structure of document
Linguistic analysis Dissects words using grammatical rules and statistics. Finds roots of words, alternate tenses, equivalent terms and likely misspellings. Related terms: stemming, morphology, synonym-handling, spell-checking.
Natural language processing Uses grammatical rules to find and understand words in a particular category like product names. More advanced approaches classify words by parts of speech to understand their meaning. Related terms: named entity extraction, semantic analysis.
Ontology Formally describes the terms, concepts and interrelationships in a particular subject area.
Probabilistic Calculates the likelihood that the terms in a given document refer to the same concepts as the terms in the query.
Taxonomy Establishes the hierarchical relationships between concepts and terms in a particular subject area.
Vector-based Represents documents and queries as arrows on a graph with a very large number of dimensions and determines relevance based on their physical proximity in the graph.
Source: Forrester Research Inc.’s Upgrade to the Right Search Engine
Click Here for the Internet Retailer Guide to Site Search Solutions