A method for recommending online products, comprising: specifying, using a processor, a main product zone of a query product image, the main product zone being a zone of pixels including a main product, wherein the specifying of the main product zone comprises: removing an image background from the specified main product zone to obtain a modified main product zone; and calculating a center of gravity of the modified main product zone, wherein the center of gravity relates to a center of the modified main product zone; dividing, based on the center of gravity, the main product zone into a plurality of local zones; extracting color features from at least one local zone of the plurality of local zones; looking up candidate recommended product images sharing common characteristics with the query product image based on the color features of the at least one local zone of the plurality of local zones; matching, among the looked up candidate recommended product images, product images that are similar in terms of color matching to the query product image, wherein the color matching is determined based on a comparison of the color features of the at least one local zone and color features of the candidate recommended product images; regarding the matched product images as recommended product images; and establishing an inverted index for the product images based on word frequencies of words in the product images, wherein: the main product zone is comprised of high-dimensional vectors, a high dimensional vector comprising a vector including a plurality of dimensions, a dimension corresponding to a color word; a vector in each dimension corresponds to a word frequency; and a probability distribution of the vector in the each dimension is quantified. specifying, using a processor, a main product zone of a query product image, the main product zone being a zone of pixels including a main product, wherein the specifying of the main product zone comprises: removing an image background from the specified main product zone to obtain a modified main product zone; and calculating a center of gravity of the modified main product zone, wherein the center of gravity relates to a center of the modified main product zone; removing an image background from the specified main product zone to obtain a modified main product zone; and calculating a center of gravity of the modified main product zone, wherein the center of gravity relates to a center of the modified main product zone; dividing, based on the center of gravity, the main product zone into a plurality of local zones; extracting color features from at least one local zone of the plurality of local zones; looking up candidate recommended product images sharing common characteristics with the query product image based on the color features of the at least one local zone of the plurality of local zones; matching, among the looked up candidate recommended product images, product images that are similar in terms of color matching to the query product image, wherein the color matching is determined based on a comparison of the color features of the at least one local zone and color features of the candidate recommended product images; regarding the matched product images as recommended product images; and establishing an inverted index for the product images based on word frequencies of words in the product images, wherein: the main product zone is comprised of high-dimensional vectors, a high dimensional vector comprising a vector including a plurality of dimensions, a dimension corresponding to a color word; a vector in each dimension corresponds to a word frequency; and a probability distribution of the vector in the each dimension is quantified. the main product zone is comprised of high-dimensional vectors, a high dimensional vector comprising a vector including a plurality of dimensions, a dimension corresponding to a color word; a vector in each dimension corresponds to a word frequency; and a probability distribution of the vector in the each dimension is quantified.